xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

3dda0058f224bd21325e698701be29d017ab6010

80

py

Python

nmt/utils/__init__.py

jojkos/neural-machine-translation

c123dbfb66314050dfbe0b0e46899ef2f44500da

[ "MIT" ]

null

nmt/utils/__init__.py

jojkos/neural-machine-translation

c123dbfb66314050dfbe0b0e46899ef2f44500da

[ "MIT" ]

null

nmt/utils/__init__.py

jojkos/neural-machine-translation

c123dbfb66314050dfbe0b0e46899ef2f44500da

[ "MIT" ]

1

2019-07-17T07:51:06.000Z

from .data_utils import * from .script_utils import * from .math_utils import *

20

27

0.775

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80

4.916667

0.5

0.559322

0.508475

0

0.15

80

3

28

26.666667

0.867647

0

1

0

true

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1

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1

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1

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null

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1

0

null

0

1

0

1

0

1

0

7

9a7c137d641c0900ffed3cdc819ad3689c661c84

40

py

Python

fancyprint/__init__.py

anthony-aylward/fancyprint

c4cf7f76260921a1dfb145bf4dd4f5272b203115

[ "MIT" ]

null

fancyprint/__init__.py

anthony-aylward/fancyprint

c4cf7f76260921a1dfb145bf4dd4f5272b203115

[ "MIT" ]

null

fancyprint/__init__.py

anthony-aylward/fancyprint

c4cf7f76260921a1dfb145bf4dd4f5272b203115

[ "MIT" ]

null

from fancyprint.fancyprint import fprint

40

0.9

5

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7.2

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0.075

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0.972973

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1

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true

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null

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null

0

1

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1

0

7

9adc6f444dd374bd95ca13187c30084e3e307c5e

51,651

py

Python

ros2_plan_t1/plan_t1/cp.py

rapa5Gclass/ddrawaddaraga

285653cfd5c4980296477710bec7f8acf404aa2d

[ "Apache-2.0" ]

null

ros2_plan_t1/plan_t1/cp.py

rapa5Gclass/ddrawaddaraga

285653cfd5c4980296477710bec7f8acf404aa2d

[ "Apache-2.0" ]

null

ros2_plan_t1/plan_t1/cp.py

rapa5Gclass/ddrawaddaraga

285653cfd5c4980296477710bec7f8acf404aa2d

[ "Apache-2.0" ]

null

# generated from rosidl_generator_py/resource/_idl.py.em # with input from nav2_msgs:action/ComputePathThroughPoses.idl # generated code does not contain a copyright notice # Import statements for member types import rosidl_parser.definition # noqa: E402, I100 class Metaclass_ComputePathThroughPoses_Goal(type): """Metaclass of message 'ComputePathThroughPoses_Goal'.""" _CREATE_ROS_MESSAGE = None _CONVERT_FROM_PY = None _CONVERT_TO_PY = None _DESTROY_ROS_MESSAGE = None _TYPE_SUPPORT = None __constants = { } @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_Goal') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._CREATE_ROS_MESSAGE = module.create_ros_message_msg__action__compute_path_through_poses__goal cls._CONVERT_FROM_PY = module.convert_from_py_msg__action__compute_path_through_poses__goal cls._CONVERT_TO_PY = module.convert_to_py_msg__action__compute_path_through_poses__goal cls._TYPE_SUPPORT = module.type_support_msg__action__compute_path_through_poses__goal cls._DESTROY_ROS_MESSAGE = module.destroy_ros_message_msg__action__compute_path_through_poses__goal from geometry_msgs.msg import PoseStamped if PoseStamped.__class__._TYPE_SUPPORT is None: PoseStamped.__class__.__import_type_support__() @classmethod def __prepare__(cls, name, bases, **kwargs): # list constant names here so that they appear in the help text of # the message class under "Data and other attributes defined here:" # as well as populate each message instance return { } class ComputePathThroughPoses_Goal(metaclass=Metaclass_ComputePathThroughPoses_Goal): """Message class 'ComputePathThroughPoses_Goal'.""" __slots__ = [ '_goals', '_start', '_planner_id', '_use_start', ] _fields_and_field_types = { 'goals': 'sequence<geometry_msgs/PoseStamped>', 'start': 'geometry_msgs/PoseStamped', 'planner_id': 'string', 'use_start': 'boolean', } SLOT_TYPES = ( rosidl_parser.definition.UnboundedSequence(rosidl_parser.definition.NamespacedType(['geometry_msgs', 'msg'], 'PoseStamped')), # noqa: E501 rosidl_parser.definition.NamespacedType(['geometry_msgs', 'msg'], 'PoseStamped'), # noqa: E501 rosidl_parser.definition.UnboundedString(), # noqa: E501 rosidl_parser.definition.BasicType('boolean'), # noqa: E501 ) def __init__(self, **kwargs): assert all('_' + key in self.__slots__ for key in kwargs.keys()), \ 'Invalid arguments passed to constructor: %s' % \ ', '.join(sorted(k for k in kwargs.keys() if '_' + k not in self.__slots__)) self.goals = kwargs.get('goals', []) from geometry_msgs.msg import PoseStamped self.start = kwargs.get('start', PoseStamped()) self.planner_id = kwargs.get('planner_id', str()) self.use_start = kwargs.get('use_start', bool()) def __repr__(self): typename = self.__class__.__module__.split('.') typename.pop() typename.append(self.__class__.__name__) args = [] for s, t in zip(self.__slots__, self.SLOT_TYPES): field = getattr(self, s) fieldstr = repr(field) # We use Python array type for fields that can be directly stored # in them, and "normal" sequences for everything else. If it is # a type that we store in an array, strip off the 'array' portion. if ( isinstance(t, rosidl_parser.definition.AbstractSequence) and isinstance(t.value_type, rosidl_parser.definition.BasicType) and t.value_type.typename in ['float', 'double', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64', 'uint64'] ): if len(field) == 0: fieldstr = '[]' else: assert fieldstr.startswith('array(') prefix = "array('X', " suffix = ')' fieldstr = fieldstr[len(prefix):-len(suffix)] args.append(s[1:] + '=' + fieldstr) return '%s(%s)' % ('.'.join(typename), ', '.join(args)) def __eq__(self, other): if not isinstance(other, self.__class__): return False if self.goals != other.goals: return False if self.start != other.start: return False if self.planner_id != other.planner_id: return False if self.use_start != other.use_start: return False return True @classmethod def get_fields_and_field_types(cls): from copy import copy return copy(cls._fields_and_field_types) @property def goals(self): """Message field 'goals'.""" return self._goals @goals.setter def goals(self, value): if __debug__: from geometry_msgs.msg import PoseStamped from collections.abc import Sequence from collections.abc import Set from collections import UserList from collections import UserString assert \ ((isinstance(value, Sequence) or isinstance(value, Set) or isinstance(value, UserList)) and not isinstance(value, str) and not isinstance(value, UserString) and all(isinstance(v, PoseStamped) for v in value) and True), \ "The 'goals' field must be a set or sequence and each value of type 'PoseStamped'" self._goals = value @property def start(self): """Message field 'start'.""" return self._start @start.setter def start(self, value): if __debug__: from geometry_msgs.msg import PoseStamped assert \ isinstance(value, PoseStamped), \ "The 'start' field must be a sub message of type 'PoseStamped'" self._start = value @property def planner_id(self): """Message field 'planner_id'.""" return self._planner_id @planner_id.setter def planner_id(self, value): if __debug__: assert \ isinstance(value, str), \ "The 'planner_id' field must be of type 'str'" self._planner_id = value @property def use_start(self): """Message field 'use_start'.""" return self._use_start @use_start.setter def use_start(self, value): if __debug__: assert \ isinstance(value, bool), \ "The 'use_start' field must be of type 'bool'" self._use_start = value # Import statements for member types # already imported above # import rosidl_parser.definition class Metaclass_ComputePathThroughPoses_Result(type): """Metaclass of message 'ComputePathThroughPoses_Result'.""" _CREATE_ROS_MESSAGE = None _CONVERT_FROM_PY = None _CONVERT_TO_PY = None _DESTROY_ROS_MESSAGE = None _TYPE_SUPPORT = None __constants = { } @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_Result') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._CREATE_ROS_MESSAGE = module.create_ros_message_msg__action__compute_path_through_poses__result cls._CONVERT_FROM_PY = module.convert_from_py_msg__action__compute_path_through_poses__result cls._CONVERT_TO_PY = module.convert_to_py_msg__action__compute_path_through_poses__result cls._TYPE_SUPPORT = module.type_support_msg__action__compute_path_through_poses__result cls._DESTROY_ROS_MESSAGE = module.destroy_ros_message_msg__action__compute_path_through_poses__result from builtin_interfaces.msg import Duration if Duration.__class__._TYPE_SUPPORT is None: Duration.__class__.__import_type_support__() from nav_msgs.msg import Path if Path.__class__._TYPE_SUPPORT is None: Path.__class__.__import_type_support__() @classmethod def __prepare__(cls, name, bases, **kwargs): # list constant names here so that they appear in the help text of # the message class under "Data and other attributes defined here:" # as well as populate each message instance return { } class ComputePathThroughPoses_Result(metaclass=Metaclass_ComputePathThroughPoses_Result): """Message class 'ComputePathThroughPoses_Result'.""" __slots__ = [ '_path', '_planning_time', ] _fields_and_field_types = { 'path': 'nav_msgs/Path', 'planning_time': 'builtin_interfaces/Duration', } SLOT_TYPES = ( rosidl_parser.definition.NamespacedType(['nav_msgs', 'msg'], 'Path'), # noqa: E501 rosidl_parser.definition.NamespacedType(['builtin_interfaces', 'msg'], 'Duration'), # noqa: E501 ) def __init__(self, **kwargs): assert all('_' + key in self.__slots__ for key in kwargs.keys()), \ 'Invalid arguments passed to constructor: %s' % \ ', '.join(sorted(k for k in kwargs.keys() if '_' + k not in self.__slots__)) from nav_msgs.msg import Path self.path = kwargs.get('path', Path()) from builtin_interfaces.msg import Duration self.planning_time = kwargs.get('planning_time', Duration()) def __repr__(self): typename = self.__class__.__module__.split('.') typename.pop() typename.append(self.__class__.__name__) args = [] for s, t in zip(self.__slots__, self.SLOT_TYPES): field = getattr(self, s) fieldstr = repr(field) # We use Python array type for fields that can be directly stored # in them, and "normal" sequences for everything else. If it is # a type that we store in an array, strip off the 'array' portion. if ( isinstance(t, rosidl_parser.definition.AbstractSequence) and isinstance(t.value_type, rosidl_parser.definition.BasicType) and t.value_type.typename in ['float', 'double', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64', 'uint64'] ): if len(field) == 0: fieldstr = '[]' else: assert fieldstr.startswith('array(') prefix = "array('X', " suffix = ')' fieldstr = fieldstr[len(prefix):-len(suffix)] args.append(s[1:] + '=' + fieldstr) return '%s(%s)' % ('.'.join(typename), ', '.join(args)) def __eq__(self, other): if not isinstance(other, self.__class__): return False if self.path != other.path: return False if self.planning_time != other.planning_time: return False return True @classmethod def get_fields_and_field_types(cls): from copy import copy return copy(cls._fields_and_field_types) @property def path(self): """Message field 'path'.""" return self._path @path.setter def path(self, value): if __debug__: from nav_msgs.msg import Path assert \ isinstance(value, Path), \ "The 'path' field must be a sub message of type 'Path'" self._path = value @property def planning_time(self): """Message field 'planning_time'.""" return self._planning_time @planning_time.setter def planning_time(self, value): if __debug__: from builtin_interfaces.msg import Duration assert \ isinstance(value, Duration), \ "The 'planning_time' field must be a sub message of type 'Duration'" self._planning_time = value # Import statements for member types # already imported above # import rosidl_parser.definition class Metaclass_ComputePathThroughPoses_Feedback(type): """Metaclass of message 'ComputePathThroughPoses_Feedback'.""" _CREATE_ROS_MESSAGE = None _CONVERT_FROM_PY = None _CONVERT_TO_PY = None _DESTROY_ROS_MESSAGE = None _TYPE_SUPPORT = None __constants = { } @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_Feedback') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._CREATE_ROS_MESSAGE = module.create_ros_message_msg__action__compute_path_through_poses__feedback cls._CONVERT_FROM_PY = module.convert_from_py_msg__action__compute_path_through_poses__feedback cls._CONVERT_TO_PY = module.convert_to_py_msg__action__compute_path_through_poses__feedback cls._TYPE_SUPPORT = module.type_support_msg__action__compute_path_through_poses__feedback cls._DESTROY_ROS_MESSAGE = module.destroy_ros_message_msg__action__compute_path_through_poses__feedback @classmethod def __prepare__(cls, name, bases, **kwargs): # list constant names here so that they appear in the help text of # the message class under "Data and other attributes defined here:" # as well as populate each message instance return { } class ComputePathThroughPoses_Feedback(metaclass=Metaclass_ComputePathThroughPoses_Feedback): """Message class 'ComputePathThroughPoses_Feedback'.""" __slots__ = [ ] _fields_and_field_types = { } SLOT_TYPES = ( ) def __init__(self, **kwargs): assert all('_' + key in self.__slots__ for key in kwargs.keys()), \ 'Invalid arguments passed to constructor: %s' % \ ', '.join(sorted(k for k in kwargs.keys() if '_' + k not in self.__slots__)) def __repr__(self): typename = self.__class__.__module__.split('.') typename.pop() typename.append(self.__class__.__name__) args = [] for s, t in zip(self.__slots__, self.SLOT_TYPES): field = getattr(self, s) fieldstr = repr(field) # We use Python array type for fields that can be directly stored # in them, and "normal" sequences for everything else. If it is # a type that we store in an array, strip off the 'array' portion. if ( isinstance(t, rosidl_parser.definition.AbstractSequence) and isinstance(t.value_type, rosidl_parser.definition.BasicType) and t.value_type.typename in ['float', 'double', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64', 'uint64'] ): if len(field) == 0: fieldstr = '[]' else: assert fieldstr.startswith('array(') prefix = "array('X', " suffix = ')' fieldstr = fieldstr[len(prefix):-len(suffix)] args.append(s[1:] + '=' + fieldstr) return '%s(%s)' % ('.'.join(typename), ', '.join(args)) def __eq__(self, other): if not isinstance(other, self.__class__): return False return True @classmethod def get_fields_and_field_types(cls): from copy import copy return copy(cls._fields_and_field_types) # Import statements for member types # already imported above # import rosidl_parser.definition class Metaclass_ComputePathThroughPoses_SendGoal_Request(type): """Metaclass of message 'ComputePathThroughPoses_SendGoal_Request'.""" _CREATE_ROS_MESSAGE = None _CONVERT_FROM_PY = None _CONVERT_TO_PY = None _DESTROY_ROS_MESSAGE = None _TYPE_SUPPORT = None __constants = { } @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_SendGoal_Request') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._CREATE_ROS_MESSAGE = module.create_ros_message_msg__action__compute_path_through_poses__send_goal__request cls._CONVERT_FROM_PY = module.convert_from_py_msg__action__compute_path_through_poses__send_goal__request cls._CONVERT_TO_PY = module.convert_to_py_msg__action__compute_path_through_poses__send_goal__request cls._TYPE_SUPPORT = module.type_support_msg__action__compute_path_through_poses__send_goal__request cls._DESTROY_ROS_MESSAGE = module.destroy_ros_message_msg__action__compute_path_through_poses__send_goal__request from nav2_msgs.action import ComputePathThroughPoses if ComputePathThroughPoses.Goal.__class__._TYPE_SUPPORT is None: ComputePathThroughPoses.Goal.__class__.__import_type_support__() from unique_identifier_msgs.msg import UUID if UUID.__class__._TYPE_SUPPORT is None: UUID.__class__.__import_type_support__() @classmethod def __prepare__(cls, name, bases, **kwargs): # list constant names here so that they appear in the help text of # the message class under "Data and other attributes defined here:" # as well as populate each message instance return { } class ComputePathThroughPoses_SendGoal_Request(metaclass=Metaclass_ComputePathThroughPoses_SendGoal_Request): """Message class 'ComputePathThroughPoses_SendGoal_Request'.""" __slots__ = [ '_goal_id', '_goal', ] _fields_and_field_types = { 'goal_id': 'unique_identifier_msgs/UUID', 'goal': 'nav2_msgs/ComputePathThroughPoses_Goal', } SLOT_TYPES = ( rosidl_parser.definition.NamespacedType(['unique_identifier_msgs', 'msg'], 'UUID'), # noqa: E501 rosidl_parser.definition.NamespacedType(['nav2_msgs', 'action'], 'ComputePathThroughPoses_Goal'), # noqa: E501 ) def __init__(self, **kwargs): assert all('_' + key in self.__slots__ for key in kwargs.keys()), \ 'Invalid arguments passed to constructor: %s' % \ ', '.join(sorted(k for k in kwargs.keys() if '_' + k not in self.__slots__)) from unique_identifier_msgs.msg import UUID self.goal_id = kwargs.get('goal_id', UUID()) from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Goal self.goal = kwargs.get('goal', ComputePathThroughPoses_Goal()) def __repr__(self): typename = self.__class__.__module__.split('.') typename.pop() typename.append(self.__class__.__name__) args = [] for s, t in zip(self.__slots__, self.SLOT_TYPES): field = getattr(self, s) fieldstr = repr(field) # We use Python array type for fields that can be directly stored # in them, and "normal" sequences for everything else. If it is # a type that we store in an array, strip off the 'array' portion. if ( isinstance(t, rosidl_parser.definition.AbstractSequence) and isinstance(t.value_type, rosidl_parser.definition.BasicType) and t.value_type.typename in ['float', 'double', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64', 'uint64'] ): if len(field) == 0: fieldstr = '[]' else: assert fieldstr.startswith('array(') prefix = "array('X', " suffix = ')' fieldstr = fieldstr[len(prefix):-len(suffix)] args.append(s[1:] + '=' + fieldstr) return '%s(%s)' % ('.'.join(typename), ', '.join(args)) def __eq__(self, other): if not isinstance(other, self.__class__): return False if self.goal_id != other.goal_id: return False if self.goal != other.goal: return False return True @classmethod def get_fields_and_field_types(cls): from copy import copy return copy(cls._fields_and_field_types) @property def goal_id(self): """Message field 'goal_id'.""" return self._goal_id @goal_id.setter def goal_id(self, value): if __debug__: from unique_identifier_msgs.msg import UUID assert \ isinstance(value, UUID), \ "The 'goal_id' field must be a sub message of type 'UUID'" self._goal_id = value @property def goal(self): """Message field 'goal'.""" return self._goal @goal.setter def goal(self, value): if __debug__: from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Goal assert \ isinstance(value, ComputePathThroughPoses_Goal), \ "The 'goal' field must be a sub message of type 'ComputePathThroughPoses_Goal'" self._goal = value # Import statements for member types # already imported above # import rosidl_parser.definition class Metaclass_ComputePathThroughPoses_SendGoal_Response(type): """Metaclass of message 'ComputePathThroughPoses_SendGoal_Response'.""" _CREATE_ROS_MESSAGE = None _CONVERT_FROM_PY = None _CONVERT_TO_PY = None _DESTROY_ROS_MESSAGE = None _TYPE_SUPPORT = None __constants = { } @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_SendGoal_Response') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._CREATE_ROS_MESSAGE = module.create_ros_message_msg__action__compute_path_through_poses__send_goal__response cls._CONVERT_FROM_PY = module.convert_from_py_msg__action__compute_path_through_poses__send_goal__response cls._CONVERT_TO_PY = module.convert_to_py_msg__action__compute_path_through_poses__send_goal__response cls._TYPE_SUPPORT = module.type_support_msg__action__compute_path_through_poses__send_goal__response cls._DESTROY_ROS_MESSAGE = module.destroy_ros_message_msg__action__compute_path_through_poses__send_goal__response from builtin_interfaces.msg import Time if Time.__class__._TYPE_SUPPORT is None: Time.__class__.__import_type_support__() @classmethod def __prepare__(cls, name, bases, **kwargs): # list constant names here so that they appear in the help text of # the message class under "Data and other attributes defined here:" # as well as populate each message instance return { } class ComputePathThroughPoses_SendGoal_Response(metaclass=Metaclass_ComputePathThroughPoses_SendGoal_Response): """Message class 'ComputePathThroughPoses_SendGoal_Response'.""" __slots__ = [ '_accepted', '_stamp', ] _fields_and_field_types = { 'accepted': 'boolean', 'stamp': 'builtin_interfaces/Time', } SLOT_TYPES = ( rosidl_parser.definition.BasicType('boolean'), # noqa: E501 rosidl_parser.definition.NamespacedType(['builtin_interfaces', 'msg'], 'Time'), # noqa: E501 ) def __init__(self, **kwargs): assert all('_' + key in self.__slots__ for key in kwargs.keys()), \ 'Invalid arguments passed to constructor: %s' % \ ', '.join(sorted(k for k in kwargs.keys() if '_' + k not in self.__slots__)) self.accepted = kwargs.get('accepted', bool()) from builtin_interfaces.msg import Time self.stamp = kwargs.get('stamp', Time()) def __repr__(self): typename = self.__class__.__module__.split('.') typename.pop() typename.append(self.__class__.__name__) args = [] for s, t in zip(self.__slots__, self.SLOT_TYPES): field = getattr(self, s) fieldstr = repr(field) # We use Python array type for fields that can be directly stored # in them, and "normal" sequences for everything else. If it is # a type that we store in an array, strip off the 'array' portion. if ( isinstance(t, rosidl_parser.definition.AbstractSequence) and isinstance(t.value_type, rosidl_parser.definition.BasicType) and t.value_type.typename in ['float', 'double', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64', 'uint64'] ): if len(field) == 0: fieldstr = '[]' else: assert fieldstr.startswith('array(') prefix = "array('X', " suffix = ')' fieldstr = fieldstr[len(prefix):-len(suffix)] args.append(s[1:] + '=' + fieldstr) return '%s(%s)' % ('.'.join(typename), ', '.join(args)) def __eq__(self, other): if not isinstance(other, self.__class__): return False if self.accepted != other.accepted: return False if self.stamp != other.stamp: return False return True @classmethod def get_fields_and_field_types(cls): from copy import copy return copy(cls._fields_and_field_types) @property def accepted(self): """Message field 'accepted'.""" return self._accepted @accepted.setter def accepted(self, value): if __debug__: assert \ isinstance(value, bool), \ "The 'accepted' field must be of type 'bool'" self._accepted = value @property def stamp(self): """Message field 'stamp'.""" return self._stamp @stamp.setter def stamp(self, value): if __debug__: from builtin_interfaces.msg import Time assert \ isinstance(value, Time), \ "The 'stamp' field must be a sub message of type 'Time'" self._stamp = value class Metaclass_ComputePathThroughPoses_SendGoal(type): """Metaclass of service 'ComputePathThroughPoses_SendGoal'.""" _TYPE_SUPPORT = None @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_SendGoal') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._TYPE_SUPPORT = module.type_support_srv__action__compute_path_through_poses__send_goal from nav2_msgs.action import _compute_path_through_poses if _compute_path_through_poses.Metaclass_ComputePathThroughPoses_SendGoal_Request._TYPE_SUPPORT is None: _compute_path_through_poses.Metaclass_ComputePathThroughPoses_SendGoal_Request.__import_type_support__() if _compute_path_through_poses.Metaclass_ComputePathThroughPoses_SendGoal_Response._TYPE_SUPPORT is None: _compute_path_through_poses.Metaclass_ComputePathThroughPoses_SendGoal_Response.__import_type_support__() class ComputePathThroughPoses_SendGoal(metaclass=Metaclass_ComputePathThroughPoses_SendGoal): from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_SendGoal_Request as Request from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_SendGoal_Response as Response def __init__(self): raise NotImplementedError('Service classes can not be instantiated') # Import statements for member types # already imported above # import rosidl_parser.definition class Metaclass_ComputePathThroughPoses_GetResult_Request(type): """Metaclass of message 'ComputePathThroughPoses_GetResult_Request'.""" _CREATE_ROS_MESSAGE = None _CONVERT_FROM_PY = None _CONVERT_TO_PY = None _DESTROY_ROS_MESSAGE = None _TYPE_SUPPORT = None __constants = { } @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_GetResult_Request') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._CREATE_ROS_MESSAGE = module.create_ros_message_msg__action__compute_path_through_poses__get_result__request cls._CONVERT_FROM_PY = module.convert_from_py_msg__action__compute_path_through_poses__get_result__request cls._CONVERT_TO_PY = module.convert_to_py_msg__action__compute_path_through_poses__get_result__request cls._TYPE_SUPPORT = module.type_support_msg__action__compute_path_through_poses__get_result__request cls._DESTROY_ROS_MESSAGE = module.destroy_ros_message_msg__action__compute_path_through_poses__get_result__request from unique_identifier_msgs.msg import UUID if UUID.__class__._TYPE_SUPPORT is None: UUID.__class__.__import_type_support__() @classmethod def __prepare__(cls, name, bases, **kwargs): # list constant names here so that they appear in the help text of # the message class under "Data and other attributes defined here:" # as well as populate each message instance return { } class ComputePathThroughPoses_GetResult_Request(metaclass=Metaclass_ComputePathThroughPoses_GetResult_Request): """Message class 'ComputePathThroughPoses_GetResult_Request'.""" __slots__ = [ '_goal_id', ] _fields_and_field_types = { 'goal_id': 'unique_identifier_msgs/UUID', } SLOT_TYPES = ( rosidl_parser.definition.NamespacedType(['unique_identifier_msgs', 'msg'], 'UUID'), # noqa: E501 ) def __init__(self, **kwargs): assert all('_' + key in self.__slots__ for key in kwargs.keys()), \ 'Invalid arguments passed to constructor: %s' % \ ', '.join(sorted(k for k in kwargs.keys() if '_' + k not in self.__slots__)) from unique_identifier_msgs.msg import UUID self.goal_id = kwargs.get('goal_id', UUID()) def __repr__(self): typename = self.__class__.__module__.split('.') typename.pop() typename.append(self.__class__.__name__) args = [] for s, t in zip(self.__slots__, self.SLOT_TYPES): field = getattr(self, s) fieldstr = repr(field) # We use Python array type for fields that can be directly stored # in them, and "normal" sequences for everything else. If it is # a type that we store in an array, strip off the 'array' portion. if ( isinstance(t, rosidl_parser.definition.AbstractSequence) and isinstance(t.value_type, rosidl_parser.definition.BasicType) and t.value_type.typename in ['float', 'double', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64', 'uint64'] ): if len(field) == 0: fieldstr = '[]' else: assert fieldstr.startswith('array(') prefix = "array('X', " suffix = ')' fieldstr = fieldstr[len(prefix):-len(suffix)] args.append(s[1:] + '=' + fieldstr) return '%s(%s)' % ('.'.join(typename), ', '.join(args)) def __eq__(self, other): if not isinstance(other, self.__class__): return False if self.goal_id != other.goal_id: return False return True @classmethod def get_fields_and_field_types(cls): from copy import copy return copy(cls._fields_and_field_types) @property def goal_id(self): """Message field 'goal_id'.""" return self._goal_id @goal_id.setter def goal_id(self, value): if __debug__: from unique_identifier_msgs.msg import UUID assert \ isinstance(value, UUID), \ "The 'goal_id' field must be a sub message of type 'UUID'" self._goal_id = value # Import statements for member types # already imported above # import rosidl_parser.definition class Metaclass_ComputePathThroughPoses_GetResult_Response(type): """Metaclass of message 'ComputePathThroughPoses_GetResult_Response'.""" _CREATE_ROS_MESSAGE = None _CONVERT_FROM_PY = None _CONVERT_TO_PY = None _DESTROY_ROS_MESSAGE = None _TYPE_SUPPORT = None __constants = { } @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_GetResult_Response') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._CREATE_ROS_MESSAGE = module.create_ros_message_msg__action__compute_path_through_poses__get_result__response cls._CONVERT_FROM_PY = module.convert_from_py_msg__action__compute_path_through_poses__get_result__response cls._CONVERT_TO_PY = module.convert_to_py_msg__action__compute_path_through_poses__get_result__response cls._TYPE_SUPPORT = module.type_support_msg__action__compute_path_through_poses__get_result__response cls._DESTROY_ROS_MESSAGE = module.destroy_ros_message_msg__action__compute_path_through_poses__get_result__response from nav2_msgs.action import ComputePathThroughPoses if ComputePathThroughPoses.Result.__class__._TYPE_SUPPORT is None: ComputePathThroughPoses.Result.__class__.__import_type_support__() @classmethod def __prepare__(cls, name, bases, **kwargs): # list constant names here so that they appear in the help text of # the message class under "Data and other attributes defined here:" # as well as populate each message instance return { } class ComputePathThroughPoses_GetResult_Response(metaclass=Metaclass_ComputePathThroughPoses_GetResult_Response): """Message class 'ComputePathThroughPoses_GetResult_Response'.""" __slots__ = [ '_status', '_result', ] _fields_and_field_types = { 'status': 'int8', 'result': 'nav2_msgs/ComputePathThroughPoses_Result', } SLOT_TYPES = ( rosidl_parser.definition.BasicType('int8'), # noqa: E501 rosidl_parser.definition.NamespacedType(['nav2_msgs', 'action'], 'ComputePathThroughPoses_Result'), # noqa: E501 ) def __init__(self, **kwargs): assert all('_' + key in self.__slots__ for key in kwargs.keys()), \ 'Invalid arguments passed to constructor: %s' % \ ', '.join(sorted(k for k in kwargs.keys() if '_' + k not in self.__slots__)) self.status = kwargs.get('status', int()) from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Result self.result = kwargs.get('result', ComputePathThroughPoses_Result()) def __repr__(self): typename = self.__class__.__module__.split('.') typename.pop() typename.append(self.__class__.__name__) args = [] for s, t in zip(self.__slots__, self.SLOT_TYPES): field = getattr(self, s) fieldstr = repr(field) # We use Python array type for fields that can be directly stored # in them, and "normal" sequences for everything else. If it is # a type that we store in an array, strip off the 'array' portion. if ( isinstance(t, rosidl_parser.definition.AbstractSequence) and isinstance(t.value_type, rosidl_parser.definition.BasicType) and t.value_type.typename in ['float', 'double', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64', 'uint64'] ): if len(field) == 0: fieldstr = '[]' else: assert fieldstr.startswith('array(') prefix = "array('X', " suffix = ')' fieldstr = fieldstr[len(prefix):-len(suffix)] args.append(s[1:] + '=' + fieldstr) return '%s(%s)' % ('.'.join(typename), ', '.join(args)) def __eq__(self, other): if not isinstance(other, self.__class__): return False if self.status != other.status: return False if self.result != other.result: return False return True @classmethod def get_fields_and_field_types(cls): from copy import copy return copy(cls._fields_and_field_types) @property def status(self): """Message field 'status'.""" return self._status @status.setter def status(self, value): if __debug__: assert \ isinstance(value, int), \ "The 'status' field must be of type 'int'" assert value >= -128 and value < 128, \ "The 'status' field must be an integer in [-128, 127]" self._status = value @property def result(self): """Message field 'result'.""" return self._result @result.setter def result(self, value): if __debug__: from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Result assert \ isinstance(value, ComputePathThroughPoses_Result), \ "The 'result' field must be a sub message of type 'ComputePathThroughPoses_Result'" self._result = value class Metaclass_ComputePathThroughPoses_GetResult(type): """Metaclass of service 'ComputePathThroughPoses_GetResult'.""" _TYPE_SUPPORT = None @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_GetResult') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._TYPE_SUPPORT = module.type_support_srv__action__compute_path_through_poses__get_result from nav2_msgs.action import _compute_path_through_poses if _compute_path_through_poses.Metaclass_ComputePathThroughPoses_GetResult_Request._TYPE_SUPPORT is None: _compute_path_through_poses.Metaclass_ComputePathThroughPoses_GetResult_Request.__import_type_support__() if _compute_path_through_poses.Metaclass_ComputePathThroughPoses_GetResult_Response._TYPE_SUPPORT is None: _compute_path_through_poses.Metaclass_ComputePathThroughPoses_GetResult_Response.__import_type_support__() class ComputePathThroughPoses_GetResult(metaclass=Metaclass_ComputePathThroughPoses_GetResult): from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_GetResult_Request as Request from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_GetResult_Response as Response def __init__(self): raise NotImplementedError('Service classes can not be instantiated') # Import statements for member types # already imported above # import rosidl_parser.definition class Metaclass_ComputePathThroughPoses_FeedbackMessage(type): """Metaclass of message 'ComputePathThroughPoses_FeedbackMessage'.""" _CREATE_ROS_MESSAGE = None _CONVERT_FROM_PY = None _CONVERT_TO_PY = None _DESTROY_ROS_MESSAGE = None _TYPE_SUPPORT = None __constants = { } @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses_FeedbackMessage') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._CREATE_ROS_MESSAGE = module.create_ros_message_msg__action__compute_path_through_poses__feedback_message cls._CONVERT_FROM_PY = module.convert_from_py_msg__action__compute_path_through_poses__feedback_message cls._CONVERT_TO_PY = module.convert_to_py_msg__action__compute_path_through_poses__feedback_message cls._TYPE_SUPPORT = module.type_support_msg__action__compute_path_through_poses__feedback_message cls._DESTROY_ROS_MESSAGE = module.destroy_ros_message_msg__action__compute_path_through_poses__feedback_message from nav2_msgs.action import ComputePathThroughPoses if ComputePathThroughPoses.Feedback.__class__._TYPE_SUPPORT is None: ComputePathThroughPoses.Feedback.__class__.__import_type_support__() from unique_identifier_msgs.msg import UUID if UUID.__class__._TYPE_SUPPORT is None: UUID.__class__.__import_type_support__() @classmethod def __prepare__(cls, name, bases, **kwargs): # list constant names here so that they appear in the help text of # the message class under "Data and other attributes defined here:" # as well as populate each message instance return { } class ComputePathThroughPoses_FeedbackMessage(metaclass=Metaclass_ComputePathThroughPoses_FeedbackMessage): """Message class 'ComputePathThroughPoses_FeedbackMessage'.""" __slots__ = [ '_goal_id', '_feedback', ] _fields_and_field_types = { 'goal_id': 'unique_identifier_msgs/UUID', 'feedback': 'nav2_msgs/ComputePathThroughPoses_Feedback', } SLOT_TYPES = ( rosidl_parser.definition.NamespacedType(['unique_identifier_msgs', 'msg'], 'UUID'), # noqa: E501 rosidl_parser.definition.NamespacedType(['nav2_msgs', 'action'], 'ComputePathThroughPoses_Feedback'), # noqa: E501 ) def __init__(self, **kwargs): assert all('_' + key in self.__slots__ for key in kwargs.keys()), \ 'Invalid arguments passed to constructor: %s' % \ ', '.join(sorted(k for k in kwargs.keys() if '_' + k not in self.__slots__)) from unique_identifier_msgs.msg import UUID self.goal_id = kwargs.get('goal_id', UUID()) from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Feedback self.feedback = kwargs.get('feedback', ComputePathThroughPoses_Feedback()) def __repr__(self): typename = self.__class__.__module__.split('.') typename.pop() typename.append(self.__class__.__name__) args = [] for s, t in zip(self.__slots__, self.SLOT_TYPES): field = getattr(self, s) fieldstr = repr(field) # We use Python array type for fields that can be directly stored # in them, and "normal" sequences for everything else. If it is # a type that we store in an array, strip off the 'array' portion. if ( isinstance(t, rosidl_parser.definition.AbstractSequence) and isinstance(t.value_type, rosidl_parser.definition.BasicType) and t.value_type.typename in ['float', 'double', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64', 'uint64'] ): if len(field) == 0: fieldstr = '[]' else: assert fieldstr.startswith('array(') prefix = "array('X', " suffix = ')' fieldstr = fieldstr[len(prefix):-len(suffix)] args.append(s[1:] + '=' + fieldstr) return '%s(%s)' % ('.'.join(typename), ', '.join(args)) def __eq__(self, other): if not isinstance(other, self.__class__): return False if self.goal_id != other.goal_id: return False if self.feedback != other.feedback: return False return True @classmethod def get_fields_and_field_types(cls): from copy import copy return copy(cls._fields_and_field_types) @property def goal_id(self): """Message field 'goal_id'.""" return self._goal_id @goal_id.setter def goal_id(self, value): if __debug__: from unique_identifier_msgs.msg import UUID assert \ isinstance(value, UUID), \ "The 'goal_id' field must be a sub message of type 'UUID'" self._goal_id = value @property def feedback(self): """Message field 'feedback'.""" return self._feedback @feedback.setter def feedback(self, value): if __debug__: from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Feedback assert \ isinstance(value, ComputePathThroughPoses_Feedback), \ "The 'feedback' field must be a sub message of type 'ComputePathThroughPoses_Feedback'" self._feedback = value class Metaclass_ComputePathThroughPoses(type): """Metaclass of action 'ComputePathThroughPoses'.""" _TYPE_SUPPORT = None @classmethod def __import_type_support__(cls): try: from rosidl_generator_py import import_type_support module = import_type_support('nav2_msgs') except ImportError: import logging import traceback logger = logging.getLogger( 'nav2_msgs.action.ComputePathThroughPoses') logger.debug( 'Failed to import needed modules for type support:\n' + traceback.format_exc()) else: cls._TYPE_SUPPORT = module.type_support_action__action__compute_path_through_poses from action_msgs.msg import _goal_status_array if _goal_status_array.Metaclass_GoalStatusArray._TYPE_SUPPORT is None: _goal_status_array.Metaclass_GoalStatusArray.__import_type_support__() from action_msgs.srv import _cancel_goal if _cancel_goal.Metaclass_CancelGoal._TYPE_SUPPORT is None: _cancel_goal.Metaclass_CancelGoal.__import_type_support__() from nav2_msgs.action import _compute_path_through_poses if _compute_path_through_poses.Metaclass_ComputePathThroughPoses_SendGoal._TYPE_SUPPORT is None: _compute_path_through_poses.Metaclass_ComputePathThroughPoses_SendGoal.__import_type_support__() if _compute_path_through_poses.Metaclass_ComputePathThroughPoses_GetResult._TYPE_SUPPORT is None: _compute_path_through_poses.Metaclass_ComputePathThroughPoses_GetResult.__import_type_support__() if _compute_path_through_poses.Metaclass_ComputePathThroughPoses_FeedbackMessage._TYPE_SUPPORT is None: _compute_path_through_poses.Metaclass_ComputePathThroughPoses_FeedbackMessage.__import_type_support__() class ComputePathThroughPoses(metaclass=Metaclass_ComputePathThroughPoses): # The goal message defined in the action definition. from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Goal as Goal # The result message defined in the action definition. from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Result as Result # The feedback message defined in the action definition. from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_Feedback as Feedback class Impl: # The send_goal service using a wrapped version of the goal message as a request. from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_SendGoal as SendGoalService # The get_result service using a wrapped version of the result message as a response. from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_GetResult as GetResultService # The feedback message with generic fields which wraps the feedback message. from nav2_msgs.action._compute_path_through_poses import ComputePathThroughPoses_FeedbackMessage as FeedbackMessage # The generic service to cancel a goal. from action_msgs.srv._cancel_goal import CancelGoal as CancelGoalService # The generic message for get the status of a goal. from action_msgs.msg._goal_status_array import GoalStatusArray as GoalStatusMessage def __init__(self): raise NotImplementedError('Action classes can not be instantiated')

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null

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9ae9d9e56180bb81a6c048f38f62bb0ab888f315

149

py

Python

nnatest_api/user/tests/test_user_view.py

marcelotrevisani/nnatest_api

e4858e2348bf041ad2bc0674a6316bf046305701

[ "MIT" ]

null

nnatest_api/user/tests/test_user_view.py

marcelotrevisani/nnatest_api

e4858e2348bf041ad2bc0674a6316bf046305701

[ "MIT" ]

null

nnatest_api/user/tests/test_user_view.py

marcelotrevisani/nnatest_api

e4858e2348bf041ad2bc0674a6316bf046305701

[ "MIT" ]

null

import pytest from django.contrib.auth import get_user_model def create_user(**params): return get_user_model().objects.create_user(**params)

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8

9af6c9cc1715b3a56859120487eebc9dcb6ff631

2,231

py

Python

pynes/tests/dec_test.py

timgates42/pyNES

e385c7189eca44b9a9e0e781b28c8562e0647b0b

[ "BSD-3-Clause" ]

1,046

2015-02-10T02:23:58.000Z

2022-03-16T02:42:02.000Z

pynes/tests/dec_test.py

mcanthony/pyNES

5f6078c02ae1fe9c6fecb4a8490f82f8c721cf3b

[ "BSD-3-Clause" ]

30

2015-02-11T15:21:10.000Z

2022-03-11T23:12:26.000Z

pynes/tests/dec_test.py

mcanthony/pyNES

5f6078c02ae1fe9c6fecb4a8490f82f8c721cf3b

[ "BSD-3-Clause" ]

132

2015-05-28T14:55:04.000Z

2021-12-09T18:58:45.000Z

# -*- coding: utf-8 -*- import unittest from pynes.compiler import lexical, syntax, semantic class DecTest(unittest.TestCase): def test_dec_zp(self): tokens = list(lexical('DEC $00')) self.assertEquals(2, len(tokens)) self.assertEquals('T_INSTRUCTION', tokens[0]['type']) self.assertEquals('T_ADDRESS', tokens[1]['type']) ast = syntax(tokens) self.assertEquals(1, len(ast)) self.assertEquals('S_ZEROPAGE', ast[0]['type']) code = semantic(ast) self.assertEquals(code, [0xc6, 0x00]) def test_dec_zpx(self): tokens = list(lexical('DEC $10,X')) self.assertEquals(4, len(tokens)) self.assertEquals('T_INSTRUCTION', tokens[0]['type']) self.assertEquals('T_ADDRESS', tokens[1]['type']) self.assertEquals('T_SEPARATOR', tokens[2]['type']) self.assertEquals('T_REGISTER', tokens[3]['type']) ast = syntax(tokens) self.assertEquals(1, len(ast)) self.assertEquals('S_ZEROPAGE_X', ast[0]['type']) code = semantic(ast) self.assertEquals(code, [0xd6, 0x10]) def test_dec_abs(self): tokens = list(lexical('DEC $1234')) self.assertEquals(2, len(tokens)) self.assertEquals('T_INSTRUCTION', tokens[0]['type']) self.assertEquals('T_ADDRESS', tokens[1]['type']) self.assertEquals('$1234', tokens[1]['value']) ast = syntax(tokens) self.assertEquals(1, len(ast)) self.assertEquals('S_ABSOLUTE', ast[0]['type']) code = semantic(ast) self.assertEquals(code, [0xce, 0x34, 0x12]) def test_dec_absx(self): tokens = list(lexical('DEC $1234,X')) self.assertEquals(4, len(tokens)) self.assertEquals('T_INSTRUCTION', tokens[0]['type']) self.assertEquals('T_ADDRESS', tokens[1]['type']) self.assertEquals('$1234', tokens[1]['value']) self.assertEquals('T_SEPARATOR', tokens[2]['type']) self.assertEquals('T_REGISTER', tokens[3]['type']) ast = syntax(tokens) self.assertEquals(1, len(ast)) self.assertEquals('S_ABSOLUTE_X', ast[0]['type']) code = semantic(ast) self.assertEquals(code, [0xde, 0x34, 0x12])

37.813559

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0.609592

270

2,231

4.940741

0.203704

0.35982

0.152924

0.110195

0.856072

0.82009

0.778111

0.713643

0

0.040758

0.219184

2,231

58

62

38.465517

0.725029

0.009413

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0.612245

0

0.133152

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0.018116

0

0.612245

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0.081633

false

0

0.040816

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0.142857

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null

1

0

1

0

null

0

1

0

8

b1177d5b97e55775ba28fb65f6792f4b5cfa2aca

3,396

py

Python

Views/TrackingPanel.py

fefelson/FelsonSports

bc0c16d63b19ffe4d468dcda5ab224013abe23fa

[ "MIT" ]

null

Views/TrackingPanel.py

fefelson/FelsonSports

bc0c16d63b19ffe4d468dcda5ab224013abe23fa

[ "MIT" ]

null

Views/TrackingPanel.py

fefelson/FelsonSports

bc0c16d63b19ffe4d468dcda5ab224013abe23fa

[ "MIT" ]

null

import matplotlib matplotlib.use('WXAgg') from matplotlib.figure import Figure from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg as NavigationToolbar2Wx import wx from pprint import pprint class NCAABTrackingPanel(wx.Panel): def __init__(self, parent, *args, **kwargs): super().__init__(parent, *args, **kwargs) self.figure = Figure() self.axes = self.figure.subplots(2,1) self.canvas = FigureCanvas(self, -1, self.figure) self.toolbar = NavigationToolbar2Wx(self.canvas) self.toolbar.Realize() sizer = wx.BoxSizer(wx.VERTICAL) sizer.Add(self.canvas, 1, wx.LEFT | wx.TOP | wx.GROW) sizer.Add(self.toolbar, 0, wx.LEFT | wx.EXPAND) self.SetSizer(sizer) self.Fit() def setPanel(self, info): for i, value in enumerate([info[hA] for hA in ("away", "home")]): name = value["name"] data = value["data"] num = [x for x in range(len(data))] colors = [] for mO in value["money"]: if mO == 1: colors.append("green") else: colors.append("red") twoWeek = [sum(data[(i-5):i])/5 for i in range(5,len(data)+1)] oneMonth = [sum(data[(i-13):i])/13 for i in range(13,len(data)+1)] self.axes[i].clear() self.axes[i].bar(num, data, color=colors) self.axes[i].grid(True) self.axes[i].axis([0, 40, -20, 20]) self.axes[i].plot([i for i in range(5,len(data)+1)], twoWeek, color="blue") self.axes[i].plot([i for i in range(13,len(data)+1)], oneMonth, color="orange") self.canvas.draw() self.canvas.Refresh() class NBATrackingPanel(wx.Panel): def __init__(self, parent, *args, **kwargs): super().__init__(parent, *args, **kwargs) self.figure = Figure() self.axes = self.figure.subplots(2,1) self.canvas = FigureCanvas(self, -1, self.figure) self.toolbar = NavigationToolbar2Wx(self.canvas) self.toolbar.Realize() sizer = wx.BoxSizer(wx.VERTICAL) sizer.Add(self.canvas, 1, wx.LEFT | wx.TOP | wx.GROW) sizer.Add(self.toolbar, 0, wx.LEFT | wx.EXPAND) self.SetSizer(sizer) self.Fit() def setPanel(self, info): for i, value in enumerate([info[hA] for hA in ("away", "home")]): name = value["name"] data = value["data"] num = [x for x in range(len(data))] colors = [] for mO in value["money"]: if mO == 1: colors.append("green") else: colors.append("red") twoWeek = [sum(data[(i-7):i])/7 for i in range(7,len(data)+1)] oneMonth = [sum(data[(i-26):i])/26 for i in range(26,len(data)+1)] self.axes[i].clear() self.axes[i].bar(num, data, color=colors) self.axes[i].grid(True) self.axes[i].axis([40, 82, -20, 20]) self.axes[i].plot([i for i in range(7,len(data)+1)], twoWeek, color="blue") self.axes[i].plot([i for i in range(26,len(data)+1)], oneMonth, color="orange") self.canvas.draw() self.canvas.Refresh()

33.294118

93

0.555654

452

3,396

4.134956

0.196903

0.059925

0.057785

0.047084

0.872124

0.82932

0.812199

0.773676

0

0.026174

0.291225

3,396

101

94

33.623762

0.750312

0

0.746667

0

0.024441

0

1

0.053333

false

0

0.08

0

0.16

0.013333

0

null

0

1

0

1

0

null

0

7

b172e7642739bc4669e10c1336c61346215a68de

90

py

Python

suitcase/mongo_embedded/conftest.py

mrakitin/suitcase-mongo

5f150dde5f3ec5f11aa0b2076113211f941dbb3f

[ "BSD-3-Clause" ]

1

2021-03-26T14:17:16.000Z

suitcase/mongo_embedded/conftest.py

mrakitin/suitcase-mongo

5f150dde5f3ec5f11aa0b2076113211f941dbb3f

[ "BSD-3-Clause" ]

15

2019-01-30T15:04:07.000Z

2019-04-29T14:23:20.000Z

suitcase/mongo_embedded/conftest.py

mrakitin/suitcase-mongo

5f150dde5f3ec5f11aa0b2076113211f941dbb3f

[ "BSD-3-Clause" ]

3

2019-06-04T16:38:12.000Z

2020-12-04T22:29:09.000Z

from bluesky.tests.conftest import RE # noqa from ophyd.tests.conftest import hw # noqa

30

45

0.777778

14

90

5

0.642857

0.371429

0.542857

0

0.155556

90

2

46

45

0.921053

0.1

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

b1ace9a1ad81c4984c3d280dae564bd7878143f5

1,681

py

Python

03.26.21 - Calculadora.py

AdamastorLinsFrancaNetto/python-iniciante

1dab7f824559e5d3db3f28b3e408d3899a5209b4

[ "MIT" ]

null

03.26.21 - Calculadora.py

AdamastorLinsFrancaNetto/python-iniciante

1dab7f824559e5d3db3f28b3e408d3899a5209b4

[ "MIT" ]

null

03.26.21 - Calculadora.py

AdamastorLinsFrancaNetto/python-iniciante

1dab7f824559e5d3db3f28b3e408d3899a5209b4

[ "MIT" ]

null

#Implemente um script Python que consista em uma calculadora básica de quatro operações (soma, subtração, multiplicação e divisão) sn='s' while sn == 's': n1=float(input('\nNúmero: ')) op=str(input('+ - * /: ')) while op != '+' and op != '-' and op != '*' and op != '/': op=str(input('Informe uma das alternativas + - * /: ')) n2=float(input('Número: ')) if op == '+': print(f'RESULTADO: {n1} + {n2} = {n1+n2}') elif op == '-': print(f'RESULTADO: {n1} - {n2} = {n1-n2}') elif op == '*': print(f'RESULTADO: {n1} * {n2} = {n1*n2}') elif op == '/': print(f'RESULTADO: {n1} / {n2} = {n1/n2}') sn=str(input('\nDeseja fazer outra operação [s/n]? ')) while sn != 's' and sn != 'S' and sn != 'n' and sn != 'N': sn=str(input('Deseja fazer outra operação [s/n]? ')) print('\nVOLTE SEMPRE!!!') #for for x in iter(int, 1): pass n1=float(input('\nNúmero: ')) op=str(input('+ - * / : ')) while op != '+' and op != '-' and op != '*' and op != '/': op=str(input('Informe uma das alternativas + - * / : ')) n2=float(input('Número: ')) if op == '+': print(f'RESULTADO: {n1} + {n2} = {n1+n2}') elif op == '-': print(f'RESULTADO: {n1} - {n2} = {n1-n2}') elif op == '*': print(f'RESULTADO: {n1} * {n2} = {n1*n2}') elif op == '/': print(f'RESULTADO: {n1} / {n2} = {n1/n2}') sn=str(input('\nDeseja fazer outra operação [S/N]? ')) while sn != 's' and sn != 'S' and sn != 'n' and sn != 'N': sn=str(input('Deseja fazer outra operação [S/N]? ')) if sn != 's' and sn != 'S': break print('\nVOLTE SEMPRE !!!')

32.960784

130

0.490184

228

1,681

3.614035

0.236842

0.07767

0.165049

0.78034

0.769417

0

0.030057

0.267698

1,681

50

131

33.62

0.639318

0.078525

0

0.75

0

0.385612

0

1

0

false

0.025

0

0.25

0

null

0

1

0

1

0

1

0

null

0

7

49655b7aa01893c16f0de6f15d47ed273d05d267

40

py

Python

gsa_pytorch/__init__.py

lucidrains/global-self-attention-network

c31594a40d9d10bad9d60dc3a87fb76bbb7b0de9

[ "MIT" ]

82

2020-10-03T00:35:22.000Z

2022-03-29T12:43:31.000Z

gsa_pytorch/__init__.py

Forsaken-core/global-self-attention-network

c31594a40d9d10bad9d60dc3a87fb76bbb7b0de9

[ "MIT" ]

3

2020-10-20T14:21:14.000Z

2020-12-31T03:57:26.000Z

gsa_pytorch/__init__.py

Forsaken-core/global-self-attention-network

c31594a40d9d10bad9d60dc3a87fb76bbb7b0de9

[ "MIT" ]

11

2020-10-07T02:34:36.000Z

2021-12-14T11:26:25.000Z

from gsa_pytorch.gsa_pytorch import GSA

20

39

0.875

7

40

4.714286

0.571429

0.606061

0

0.1

40

1

40

0.916667

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

499fd4658dcc008654676e21c6245144a127b2fd

24,912

py

Python

tests/tests_dataprovider_integration.py

Open-CMMS/openCMMS_backend

56511ebac83a5dc1fb8768a98bc675e88530a447

[ "BSD-3-Clause" ]

3

2021-03-08T19:14:38.000Z

2022-02-01T17:57:31.000Z

tests/tests_dataprovider_integration.py

Open-CMMS/openCMMS_backend

56511ebac83a5dc1fb8768a98bc675e88530a447

[ "BSD-3-Clause" ]

null

tests/tests_dataprovider_integration.py

Open-CMMS/openCMMS_backend

56511ebac83a5dc1fb8768a98bc675e88530a447

[ "BSD-3-Clause" ]

null

import os import pytest from init_db_tests import init_db from django.contrib.auth.models import Permission from django.test import TestCase from maintenancemanagement.models import Equipment, Field from openCMMS.settings import BASE_DIR from rest_framework.test import APIClient from usersmanagement.models import UserProfile from utils.data_provider import add_job, scheduler from utils.models import DataProvider from utils.serializers import ( DataProviderRequirementsSerializer, DataProviderSerializer, ) class DataProviderTest(TestCase): @pytest.fixture(scope="class", autouse=True) def init_database(django_db_setup, django_db_blocker): with django_db_blocker.unblock(): init_db() def add_view_perm(self, user): """ Add view permission to user """ perm_view = Permission.objects.get(codename="view_dataprovider") user.user_permissions.set([perm_view]) def add_add_perm(self, user): """ Add add permission to user """ perm_add = Permission.objects.get(codename="add_dataprovider") user.user_permissions.add(perm_add) def add_change_perm(self, user): """ Add change permission to user """ perm_change = Permission.objects.get(codename="change_dataprovider") user.user_permissions.set([perm_change]) def add_delete_perm(self, user): """ Add delete permission to user """ perm_delete = Permission.objects.get(codename="delete_dataprovider") user.user_permissions.set([perm_delete]) def test_US23_I1_dataproviderlist_get_with_perm(self): """ Test if a user with perm receive the dataproviders' list Inputs: user (UserProfile): a UserProfile with permissions to view data providers. serializer (DataProviderRequirementsSerializer): a serializer containing all data providers of the database. Expected Output: We expect a 200 status code in the response. We expect to get in the response the same data as in serializer. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_view_perm(user) python_files = os.listdir(os.path.join(BASE_DIR, 'utils/data_providers')) python_files.pop(python_files.index('__init__.py')) if '__pycache__' in python_files: python_files.pop(python_files.index('__pycache__')) equipments = Equipment.objects.all() data_providers = DataProvider.objects.all() serializer = DataProviderRequirementsSerializer({'equipments': equipments, 'data_providers': data_providers}) dict_res = serializer.data.copy() dict_res['python_files'] = python_files c = APIClient() c.force_authenticate(user=user) response = c.get("/api/dataproviders/") self.assertEqual(response.status_code, 200) self.assertEqual(dict_res, response.json()) def test_US23_I1_dataproviderlist_get_without_perm(self): """ Test if a user without perm doesn't receive the dataproviders' list Inputs: user (UserProfile): a UserProfile without permissions to view data providers. Expected Output: We expect a 401 status code in the response. """ user = UserProfile.objects.create(username="user", password="p4ssword") c = APIClient() c.force_authenticate(user=user) response = c.get("/api/dataproviders/") self.assertEqual(response.status_code, 401) def test_US23_I2_dataproviderlist_post_with_perm(self): """ Test if a user with perm can add a dataprovider Inputs: user (UserProfile): a UserProfile with permissions to add data providers. serializer (DataProviderSerializer): a serializer containing the posted data provider data. post data (JSON): a mock-up of a data provider. Expected Output: We expect a 201 status code in the response. We expect to get in the response the same data as in serializer. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) response = client.post( '/api/dataproviders/', { 'file_name': 'python_file.py', 'name': 'dataprovider de test', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) dataprovider = DataProvider.objects.get(file_name='python_file.py') serializer = DataProviderSerializer(dataprovider) self.assertEqual(response.status_code, 201) self.assertEqual(response.data, serializer.data) def test_US23_I2_dataproviderlist_post_without_perm(self): """ Test if a user without perm can't add a dataprovider Inputs: user (UserProfile): a UserProfile without permissions to add data providers. post data (JSON): a mock-up of a data provider. Expected Output: We expect a 401 status code in the response. """ user = UserProfile.objects.create(username="user", password="p4ssword") client = APIClient() client.force_authenticate(user=user) response = client.post( '/api/dataproviders/', { 'file_name': 'script.py', 'name': 'dataprovider de test', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) self.assertEqual(response.status_code, 401) def test_US23_I2_dataproviderlist_post_with_perm_and_missing_parms(self): """ Test if a user with perm can't add a dataprovider whith missing params Inputs: user (UserProfile): a UserProfile with permissions to add data providers. post data (JSON): a mock-up of a data provider with missing params. Expected Output: We expect a 400 status code in the response. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) response = client.post( '/api/dataproviders/', { 'file_name': 'script.py', 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, }, format='json' ) self.assertEqual(response.status_code, 400) def test_US23_I2_dataproviderlist_post_with_perm_and_too_much_parms(self): """ Test if a user with perm can add a dataprovider whith too much params Inputs: user (UserProfile): a UserProfile with permissions to add data providers. serializer (DataProviderSerializer): a serializer containing the posted data provider data. post data (JSON): a mock-up of a data provider with too much params. Expected Output: We expect a 201 status code in the response. We expect to get in the response the same data as in serializer. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) response = client.post( '/api/dataproviders/', { 'file_name': 'script.py', 'name': 'dataprovider de test', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'fake field': 'useless data', 'is_activated': True }, format='json' ) self.assertEqual(response.status_code, 201) dataprovider = DataProvider.objects.get(file_name='script.py') serializer = DataProviderSerializer(dataprovider) self.assertEqual(response.data, serializer.data) def test_US23_I3_dataproviderdetail_get_with_perm(self): """ Test if a user with perm can get a dataprovider. Inputs: user (UserProfile): a UserProfile with permissions to view data providers. dataprovider (DataProvider): the data provider for which we want details. serializer (DataProviderSerializer): a serializer containing the data of dataprovider. Expected Output: We expect a 200 status code in the response. We expect to get in the response the same data as in serializer. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_view_perm(user) client = APIClient() client.force_authenticate(user=user) dataprovider = DataProvider.objects.get(file_name="fichier_test_dataprovider.py") serializer = DataProviderSerializer(dataprovider) response = client.get(f'/api/dataproviders/{dataprovider.id}/') self.assertEqual(response.status_code, 200) self.assertEqual(response.data, serializer.data) def test_US23_I3_dataproviderdetail_get_without_perm(self): """ Test if a user without perm can't get a dataprovider. Inputs: user (UserProfile): a UserProfile without permissions to view data providers. dataprovider (DataProvider): the data provider for which we want details. Expected Output: We expect a 401 status code in the response. """ user = UserProfile.objects.create(username="user", password="p4ssword") client = APIClient() client.force_authenticate(user=user) dataprovider = DataProvider.objects.get(file_name="fichier_test_dataprovider.py") response = client.get(f'/api/dataproviders/{dataprovider.id}/') self.assertEqual(response.status_code, 401) def test_US23_I4_dataproviderdetail_put_with_perm(self): """ Test if a user with perm can update a dataprovider. Inputs: user (UserProfile): a UserProfile with permissions to add and change data providers. serializer (DataProviderSerializer): a serializer containing the data of the updated data provider. post data (JSON): a mock-up of a data provider. put data (JSON): a mock-up of an updated data provider. Expected Output: We expect a 200 status code in the response. We expect to get in the response the same data as in serializer. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_change_perm(user) self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) client.post( '/api/dataproviders/', { 'file_name': 'python_file.py', 'name': 'dataprovider de test pour put', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) dataprovider = DataProvider.objects.get(name='dataprovider de test pour put') response = client.put( f'/api/dataproviders/{dataprovider.id}/', { 'file_name': 'fichier_test_dataprovider.py', 'name': 'dataprovider mis à jour', 'recurrence': '5d', 'ip_address': '192.168.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) dataprovider = DataProvider.objects.get(name='dataprovider mis à jour') serializer = DataProviderSerializer(dataprovider) self.assertEqual(response.status_code, 200) self.assertEqual(response.data, serializer.data) def test_US23_I4_dataproviderdetail_put_with_perm_and_missing_parms(self): """ Test if a user with perm can update a dataprovider with missing params. Inputs: user (UserProfile): a UserProfile with permissions to add and change data providers. serializer (DataProviderSerializer): a serializer containing the data of the updated data provider. post data (JSON): a mock-up of a data provider. put data (JSON): a mock-up of an updated data provider with missing params. Expected Output: We expect a 200 status code in the response. We expect to get in the response the same data as in serializer. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_change_perm(user) self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) client.post( '/api/dataproviders/', { 'file_name': 'python_file.py', 'name': 'dataprovider de test pour put', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) dataprovider = DataProvider.objects.get(name='dataprovider de test pour put') response = client.put( f'/api/dataproviders/{dataprovider.id}/', { 'name': 'dataprovider mis à jour 2', 'ip_address': '192.168.1.2', }, format='json' ) dataprovider = DataProvider.objects.get(name='dataprovider mis à jour 2') serializer = DataProviderSerializer(dataprovider) self.assertEqual(response.status_code, 200) self.assertEqual(response.data, serializer.data) def test_US23_I5_dataproviderdetail_delete_with_perm(self): """ Test if a user with perm can delete a dataprovider. Inputs: user (UserProfile): a UserProfile with permissions to delete data providers. Expected Output: We expect a 204 status code in the response. We expect to not find in database the deleted data provider. We expect to have one job less after deleted tha data provider. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_delete_perm(user) client = APIClient() client.force_authenticate(user=user) dataprovider = DataProvider.objects.get(file_name="fichier_test_dataprovider.py") add_job(dataprovider) n_jobs_before = scheduler.get_jobs() response = client.delete(f'/api/dataproviders/{dataprovider.id}/') n_jobs_after = scheduler.get_jobs() self.assertEqual(response.status_code, 204) self.assertFalse(DataProvider.objects.filter(id=dataprovider.id).exists()) self.assertEqual(len(n_jobs_before), len(n_jobs_after) + 1) def test_US23_I5_dataproviderdetail_delete_without_perm(self): """ Test if a user without perm can't delete a dataprovider. Inputs: user (UserProfile): a UserProfile without permissions to delete data providers. Expected Output: We expect a 401 status code in the response. """ user = UserProfile.objects.create(username="user", password="p4ssword") client = APIClient() client.force_authenticate(user=user) dataprovider = DataProvider.objects.get(file_name="fichier_test_dataprovider.py") response = client.delete(f'/api/dataproviders/{dataprovider.id}/') self.assertEqual(response.status_code, 401) def test_US23_I6_testdataprovider_post_with_perm(self): """ Test if a user with perm can test a data provider. Inputs: user (UserProfile): a UserProfile with permissions to add data providers. file (File): a temporary file which will return a value for the data provider test. post data (JSON): a mock-up of a data provider. Expected Output: We expect a 200 status code in the response. We expect to get in the response the value returned by get_data function in the file. """ with open(os.path.join(BASE_DIR, 'utils/data_providers/temp_test_data_providers.py'), "w+") as file: file.write('def get_data(ip_address, port):\n') file.write(' return 2') user = UserProfile.objects.create(username="user", password="p4ssword") self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) response = client.post( f'/api/dataproviders/test/', { 'file_name': 'temp_test_data_providers.py', 'name': 'dataprovider de test', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) self.assertEqual(response.status_code, 200) self.assertEqual(response.data["data"], 2) os.remove(os.path.join(BASE_DIR, 'utils/data_providers/temp_test_data_providers.py')) def test_US23_I6_testdataprovider_post_without_perm(self): """ Test if a user without perm can't test a data provider. Inputs: user (UserProfile): a UserProfile without permissions to add data providers. Expected Output: We expect a 401 status code in the response. """ user = UserProfile.objects.create(username="user", password="p4ssword") client = APIClient() client.force_authenticate(user=user) response = client.post(f'/api/dataproviders/test/', format='json') self.assertEqual(response.status_code, 401) def test_US23_I6_testdataprovider_post_with_perm_and_not_well_formated_file(self): """ Test if a user with perm can test a data provider with a not well formted file. Inputs: user (UserProfile): a UserProfile with permissions to add data providers. file (File): a temporary file which is not well formated. post data (JSON): a mock-up of a data provider. Expected Output: We expect to find the pair {'error': 'Python file is not well formated, please follow the example'} in the error of the response's data. """ with open(os.path.join(BASE_DIR, 'utils/data_providers/temp_test_data_providers_error.py'), "w+") as file: file.write('def wrong_get_data(ip_address, port):\n') file.write(' return 2') user = UserProfile.objects.create(username="user", password="p4ssword") self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) response = client.post( f'/api/dataproviders/test/', { 'file_name': 'temp_test_data_providers_error.py', 'name': 'dataprovider de test', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) self.assertEqual(response.data["error"], 'Python file is not well formated, please follow the example') os.remove(os.path.join(BASE_DIR, 'utils/data_providers/temp_test_data_providers_error.py')) def test_US23_I6_testdataprovider_post_with_perm_but_no_file(self): """ Test if a user with perm can test a data provider with missing file. Inputs: user (UserProfile): a UserProfile with permissions to add data providers. post data (JSON): a mock-up of a data provider. Expected Output: We expect to find the pair {'error': "Python file not found, please enter 'name_of_your_file.py'"} in the error of the response's data. """ user = UserProfile.objects.create(username="user", password="p4ssword") self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) response = client.post( f'/api/dataproviders/test/', { 'file_name': 'toto.py', 'name': 'dataprovider de test', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) self.assertEqual(response.data["error"], "Python file not found, please enter 'name_of_your_file.py'") def test_US23_I6_testdataprovider_post_with_perm_and_not_working_get_data(self): """ Test if a user with perm can test a data provider with a not working get_data function. Inputs: user (UserProfile): a UserProfile with permissions to add data providers. file (File): a temporary file in which doesn't work. post data (JSON): a mock-up of a data provider. Expected Output: We expect to find the pair {'error': 'IP not found or python file not working'} in the error of the response's data. """ with open( os.path.join(BASE_DIR, 'utils/data_providers/temp_test_data_providers_error_in_getdata.py'), "w+" ) as file: file.write('from utils.data_provider import GetDataException\n') file.write('def get_data(ip_address, port):\n') file.write(' raise GetDataException()') user = UserProfile.objects.create(username="user", password="p4ssword") self.add_add_perm(user) client = APIClient() client.force_authenticate(user=user) response = client.post( f'/api/dataproviders/test/', { 'file_name': 'temp_test_data_providers_error_in_getdata.py', 'name': 'dataprovider de test', 'recurrence': '10d', 'ip_address': '127.0.0.1', 'port': 5002, 'equipment': Equipment.objects.get(name='Embouteilleuse AXB1').id, 'field_object': Field.objects.get(name="Nb bouteilles").object_set.get().id, 'is_activated': True }, format='json' ) self.assertEqual(response.data["error"], 'IP not found or python file not working') os.remove(os.path.join(BASE_DIR, 'utils/data_providers/temp_test_data_providers_error_in_getdata.py'))

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77299809b26ce62dc1fe864f8dd4e5686e21f77b

76,651

py

Python

objectModel/Python/tests/cdm/resolution_guidance/test_resolution_guidance_cardinality.py

MiguelSHS/microsoftCDM

d8df31fa455fcc6afd698e3ca7ec0f8c4a6716fd

[ "CC-BY-4.0", "MIT" ]

1

2021-03-05T03:35:58.000Z

objectModel/Python/tests/cdm/resolution_guidance/test_resolution_guidance_cardinality.py

spbast/CDM

bf97a3720c97ee4c9df3625084cf8b3bc65ff9c7

[ "CC-BY-4.0", "MIT" ]

38

2021-09-07T21:23:21.000Z

2022-03-14T01:36:58.000Z

objectModel/Python/tests/cdm/resolution_guidance/test_resolution_guidance_cardinality.py

spbast/CDM

bf97a3720c97ee4c9df3625084cf8b3bc65ff9c7

[ "CC-BY-4.0", "MIT" ]

null

# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. from tests.cdm.resolution_guidance import common_test from tests.common import async_test from tests.utilities.object_validator import AttributeContextExpectedValue, AttributeExpectedValue class ResolutionGuidanceCardinalityTest(common_test.CommonTest): @async_test async def test_foreign_key_one_to_one_cardinality(self): """Resolution Guidance Test - One:One Cardinality""" test_name = 'test_foreign_key_one_to_one_cardinality' entity_name = 'Person' expectedContext_default = AttributeContextExpectedValue() expectedContext_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly = AttributeContextExpectedValue() expectedContext_structured = AttributeContextExpectedValue() expectedContext_normalized_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized_structured = AttributeContextExpectedValue() expected_default = [] expected_normalized = [] expected_referenceOnly = [] expected_structured = [] expected_normalized_structured = [] expected_referenceOnly_normalized = [] expected_referenceOnly_structured = [] expected_referenceOnly_normalized_structured = [] await self.run_test_with_values( test_name, entity_name, expectedContext_default, expectedContext_normalized, expectedContext_referenceOnly, expectedContext_structured, expectedContext_normalized_structured, expectedContext_referenceOnly_normalized, expectedContext_referenceOnly_structured, expectedContext_referenceOnly_normalized_structured, expected_default, expected_normalized, expected_referenceOnly, expected_structured, expected_normalized_structured, expected_referenceOnly_normalized, expected_referenceOnly_structured, expected_referenceOnly_normalized_structured ) entity_name = 'PersonContact' expectedContext_default = AttributeContextExpectedValue() expectedContext_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly = AttributeContextExpectedValue() expectedContext_structured = AttributeContextExpectedValue() expectedContext_normalized_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized_structured = AttributeContextExpectedValue() expected_default = [] expected_normalized = [] expected_referenceOnly = [] expected_structured = [] expected_normalized_structured = [] expected_referenceOnly_normalized = [] expected_referenceOnly_structured = [] expected_referenceOnly_normalized_structured = [] await self.run_test_with_values( test_name, entity_name, expectedContext_default, expectedContext_normalized, expectedContext_referenceOnly, expectedContext_structured, expectedContext_normalized_structured, expectedContext_referenceOnly_normalized, expectedContext_referenceOnly_structured, expectedContext_referenceOnly_normalized_structured, expected_default, expected_normalized, expected_referenceOnly, expected_structured, expected_normalized_structured, expected_referenceOnly_normalized, expected_referenceOnly_structured, expected_referenceOnly_normalized_structured ) @async_test async def test_foreign_key_many_to_many_cardinality(self): """Resolution Guidance Test - Many:Many Cardinality""" test_name = 'test_foreign_key_many_to_many_cardinality' entity_name = 'Customer' expectedContext_default = AttributeContextExpectedValue() expectedContext_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly = AttributeContextExpectedValue() expectedContext_structured = AttributeContextExpectedValue() expectedContext_normalized_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized_structured = AttributeContextExpectedValue() expected_default = [] expected_normalized = [] expected_referenceOnly = [] expected_structured = [] expected_normalized_structured = [] expected_referenceOnly_normalized = [] expected_referenceOnly_structured = [] expected_referenceOnly_normalized_structured = [] await self.run_test_with_values( test_name, entity_name, expectedContext_default, expectedContext_normalized, expectedContext_referenceOnly, expectedContext_structured, expectedContext_normalized_structured, expectedContext_referenceOnly_normalized, expectedContext_referenceOnly_structured, expectedContext_referenceOnly_normalized_structured, expected_default, expected_normalized, expected_referenceOnly, expected_structured, expected_normalized_structured, expected_referenceOnly_normalized, expected_referenceOnly_structured, expected_referenceOnly_normalized_structured ) entity_name = 'Product' expectedContext_default = AttributeContextExpectedValue() expectedContext_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly = AttributeContextExpectedValue() expectedContext_structured = AttributeContextExpectedValue() expectedContext_normalized_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized_structured = AttributeContextExpectedValue() expected_default = [] expected_normalized = [] expected_referenceOnly = [] expected_structured = [] expected_normalized_structured = [] expected_referenceOnly_normalized = [] expected_referenceOnly_structured = [] expected_referenceOnly_normalized_structured = [] await self.run_test_with_values( test_name, entity_name, expectedContext_default, expectedContext_normalized, expectedContext_referenceOnly, expectedContext_structured, expectedContext_normalized_structured, expectedContext_referenceOnly_normalized, expectedContext_referenceOnly_structured, expectedContext_referenceOnly_normalized_structured, expected_default, expected_normalized, expected_referenceOnly, expected_structured, expected_normalized_structured, expected_referenceOnly_normalized, expected_referenceOnly_structured, expected_referenceOnly_normalized_structured ) entity_name = 'Sales' expectedContext_default = AttributeContextExpectedValue() expectedContext_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly = AttributeContextExpectedValue() expectedContext_structured = AttributeContextExpectedValue() expectedContext_normalized_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized_structured = AttributeContextExpectedValue() expected_default = [] expected_normalized = [] expected_referenceOnly = [] expected_structured = [] expected_normalized_structured = [] expected_referenceOnly_normalized = [] expected_referenceOnly_structured = [] expected_referenceOnly_normalized_structured = [] await self.run_test_with_values( test_name, entity_name, expectedContext_default, expectedContext_normalized, expectedContext_referenceOnly, expectedContext_structured, expectedContext_normalized_structured, expectedContext_referenceOnly_normalized, expectedContext_referenceOnly_structured, expectedContext_referenceOnly_normalized_structured, expected_default, expected_normalized, expected_referenceOnly, expected_structured, expected_normalized_structured, expected_referenceOnly_normalized, expected_referenceOnly_structured, expected_referenceOnly_normalized_structured ) @async_test async def test_foreign_key_one_to_many_cardinality(self): """Resolution Guidance Test - One:Many Cardinality""" test_name = 'test_foreign_key_one_to_many_cardinality' entity_name = 'Team' expectedContext_default = AttributeContextExpectedValue() expectedContext_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly = AttributeContextExpectedValue() expectedContext_structured = AttributeContextExpectedValue() expectedContext_normalized_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized_structured = AttributeContextExpectedValue() expected_default = [] expected_normalized = [] expected_referenceOnly = [] expected_structured = [] expected_normalized_structured = [] expected_referenceOnly_normalized = [] expected_referenceOnly_structured = [] expected_referenceOnly_normalized_structured = [] await self.run_test_with_values( test_name, entity_name, expectedContext_default, expectedContext_normalized, expectedContext_referenceOnly, expectedContext_structured, expectedContext_normalized_structured, expectedContext_referenceOnly_normalized, expectedContext_referenceOnly_structured, expectedContext_referenceOnly_normalized_structured, expected_default, expected_normalized, expected_referenceOnly, expected_structured, expected_normalized_structured, expected_referenceOnly_normalized, expected_referenceOnly_structured, expected_referenceOnly_normalized_structured ) entity_name = 'Employee' expectedContext_default = AttributeContextExpectedValue() expectedContext_default.type = 'entity' expectedContext_default.name = 'Employee_Resolved_default' expectedContext_default.definition = 'resolvedFrom/Employee' expectedContext_default.contexts = [] attrCtx_LVL0_IND0 = AttributeContextExpectedValue() attrCtx_LVL0_IND0.type = 'entityReferenceExtends' attrCtx_LVL0_IND0.name = 'extends' attrCtx_LVL0_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default' attrCtx_LVL0_IND0.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'entity' attrCtx_LVL1_IND0.name = 'CdmEntity' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/extends' attrCtx_LVL1_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL0_IND0.contexts.append(attrCtx_LVL1_IND0) expectedContext_default.contexts.append(attrCtx_LVL0_IND0) attrCtx_LVL0_IND1 = AttributeContextExpectedValue() attrCtx_LVL0_IND1.type = 'attributeDefinition' attrCtx_LVL0_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL0_IND1.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default' attrCtx_LVL0_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL0_IND1.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'attributeGroup' attrCtx_LVL1_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope' attrCtx_LVL1_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL1_IND0.contexts = [] attrCtx_LVL2_IND0 = AttributeContextExpectedValue() attrCtx_LVL2_IND0.type = 'attributeDefinition' attrCtx_LVL2_IND0.name = 'ID' attrCtx_LVL2_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL2_IND0.context_strings = [] attrCtx_LVL2_IND0.context_strings.append('Employee_Resolved_default/hasAttributes/ID') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND0) attrCtx_LVL2_IND1 = AttributeContextExpectedValue() attrCtx_LVL2_IND1.type = 'attributeDefinition' attrCtx_LVL2_IND1.name = 'FullName' attrCtx_LVL2_IND1.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/FullName' attrCtx_LVL2_IND1.context_strings = [] attrCtx_LVL2_IND1.context_strings.append('Employee_Resolved_default/hasAttributes/FullName') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND1) attrCtx_LVL2_IND2 = AttributeContextExpectedValue() attrCtx_LVL2_IND2.type = 'attributeDefinition' attrCtx_LVL2_IND2.name = 'TeamID' attrCtx_LVL2_IND2.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND2.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID' attrCtx_LVL2_IND2.contexts = [] attrCtx_LVL3_IND0 = AttributeContextExpectedValue() attrCtx_LVL3_IND0.type = 'entity' attrCtx_LVL3_IND0.name = 'Team' attrCtx_LVL3_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND0.definition = 'resolvedFrom/Team' attrCtx_LVL3_IND0.contexts = [] attrCtx_LVL4_IND0 = AttributeContextExpectedValue() attrCtx_LVL4_IND0.type = 'entityReferenceExtends' attrCtx_LVL4_IND0.name = 'extends' attrCtx_LVL4_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team' attrCtx_LVL4_IND0.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'entity' attrCtx_LVL5_IND0.name = 'CdmEntity' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/extends' attrCtx_LVL5_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL4_IND0.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND0.contexts.append(attrCtx_LVL4_IND0) attrCtx_LVL4_IND1 = AttributeContextExpectedValue() attrCtx_LVL4_IND1.type = 'attributeDefinition' attrCtx_LVL4_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL4_IND1.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team' attrCtx_LVL4_IND1.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL4_IND1.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'attributeGroup' attrCtx_LVL5_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope' attrCtx_LVL5_IND0.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL5_IND0.contexts = [] attrCtx_LVL6_IND0 = AttributeContextExpectedValue() attrCtx_LVL6_IND0.type = 'attributeDefinition' attrCtx_LVL6_IND0.name = 'ID' attrCtx_LVL6_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL6_IND0.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL5_IND0.contexts.append(attrCtx_LVL6_IND0) attrCtx_LVL6_IND1 = AttributeContextExpectedValue() attrCtx_LVL6_IND1.type = 'attributeDefinition' attrCtx_LVL6_IND1.name = 'Name' attrCtx_LVL6_IND1.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL6_IND1.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope/members/Name' attrCtx_LVL5_IND0.contexts.append(attrCtx_LVL6_IND1) attrCtx_LVL4_IND1.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND0.contexts.append(attrCtx_LVL4_IND1) attrCtx_LVL2_IND2.contexts.append(attrCtx_LVL3_IND0) attrCtx_LVL3_IND1 = AttributeContextExpectedValue() attrCtx_LVL3_IND1.type = 'generatedSet' attrCtx_LVL3_IND1.name = '_generatedAttributeSet' attrCtx_LVL3_IND1.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND1.contexts = [] attrCtx_LVL4_IND0 = AttributeContextExpectedValue() attrCtx_LVL4_IND0.type = 'addedAttributeExpansionTotal' attrCtx_LVL4_IND0.name = 'TeamIDTeamCount' attrCtx_LVL4_IND0.parent = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/_generatedAttributeSet' attrCtx_LVL4_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID/resolutionGuidance/countAttribute/TeamCount' attrCtx_LVL4_IND0.context_strings = [] attrCtx_LVL4_IND0.context_strings.append('Employee_Resolved_default/hasAttributes/TeamIDTeamCount') attrCtx_LVL3_IND1.contexts.append(attrCtx_LVL4_IND0) attrCtx_LVL2_IND2.contexts.append(attrCtx_LVL3_IND1) attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND2) attrCtx_LVL0_IND1.contexts.append(attrCtx_LVL1_IND0) expectedContext_default.contexts.append(attrCtx_LVL0_IND1) expectedContext_normalized = AttributeContextExpectedValue() expectedContext_normalized.type = 'entity' expectedContext_normalized.name = 'Employee_Resolved_normalized' expectedContext_normalized.definition = 'resolvedFrom/Employee' expectedContext_normalized.contexts = [] attrCtx_LVL0_IND0 = AttributeContextExpectedValue() attrCtx_LVL0_IND0.type = 'entityReferenceExtends' attrCtx_LVL0_IND0.name = 'extends' attrCtx_LVL0_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized' attrCtx_LVL0_IND0.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'entity' attrCtx_LVL1_IND0.name = 'CdmEntity' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/extends' attrCtx_LVL1_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL0_IND0.contexts.append(attrCtx_LVL1_IND0) expectedContext_normalized.contexts.append(attrCtx_LVL0_IND0) attrCtx_LVL0_IND1 = AttributeContextExpectedValue() attrCtx_LVL0_IND1.type = 'attributeDefinition' attrCtx_LVL0_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL0_IND1.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized' attrCtx_LVL0_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL0_IND1.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'attributeGroup' attrCtx_LVL1_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope' attrCtx_LVL1_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL1_IND0.contexts = [] attrCtx_LVL2_IND0 = AttributeContextExpectedValue() attrCtx_LVL2_IND0.type = 'attributeDefinition' attrCtx_LVL2_IND0.name = 'TeamID' attrCtx_LVL2_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID' attrCtx_LVL2_IND0.contexts = [] attrCtx_LVL3_IND0 = AttributeContextExpectedValue() attrCtx_LVL3_IND0.type = 'entity' attrCtx_LVL3_IND0.name = 'Team' attrCtx_LVL3_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND0.definition = 'resolvedFrom/Team' attrCtx_LVL3_IND0.contexts = [] attrCtx_LVL4_IND0 = AttributeContextExpectedValue() attrCtx_LVL4_IND0.type = 'entityReferenceExtends' attrCtx_LVL4_IND0.name = 'extends' attrCtx_LVL4_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team' attrCtx_LVL4_IND0.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'entity' attrCtx_LVL5_IND0.name = 'CdmEntity' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/extends' attrCtx_LVL5_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL4_IND0.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND0.contexts.append(attrCtx_LVL4_IND0) attrCtx_LVL4_IND1 = AttributeContextExpectedValue() attrCtx_LVL4_IND1.type = 'attributeDefinition' attrCtx_LVL4_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL4_IND1.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team' attrCtx_LVL4_IND1.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL4_IND1.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'attributeGroup' attrCtx_LVL5_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope' attrCtx_LVL5_IND0.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL5_IND0.contexts = [] attrCtx_LVL6_IND0 = AttributeContextExpectedValue() attrCtx_LVL6_IND0.type = 'attributeDefinition' attrCtx_LVL6_IND0.name = 'ID' attrCtx_LVL6_IND0.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL6_IND0.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL5_IND0.contexts.append(attrCtx_LVL6_IND0) attrCtx_LVL6_IND1 = AttributeContextExpectedValue() attrCtx_LVL6_IND1.type = 'attributeDefinition' attrCtx_LVL6_IND1.name = 'Name' attrCtx_LVL6_IND1.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL6_IND1.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope/members/Name' attrCtx_LVL5_IND0.contexts.append(attrCtx_LVL6_IND1) attrCtx_LVL4_IND1.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND0.contexts.append(attrCtx_LVL4_IND1) attrCtx_LVL2_IND0.contexts.append(attrCtx_LVL3_IND0) attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND0) attrCtx_LVL2_IND1 = AttributeContextExpectedValue() attrCtx_LVL2_IND1.type = 'attributeDefinition' attrCtx_LVL2_IND1.name = 'ID' attrCtx_LVL2_IND1.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL2_IND1.context_strings = [] attrCtx_LVL2_IND1.context_strings.append('Employee_Resolved_normalized/hasAttributes/ID') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND1) attrCtx_LVL2_IND2 = AttributeContextExpectedValue() attrCtx_LVL2_IND2.type = 'attributeDefinition' attrCtx_LVL2_IND2.name = 'FullName' attrCtx_LVL2_IND2.parent = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND2.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/FullName' attrCtx_LVL2_IND2.context_strings = [] attrCtx_LVL2_IND2.context_strings.append('Employee_Resolved_normalized/hasAttributes/FullName') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND2) attrCtx_LVL0_IND1.contexts.append(attrCtx_LVL1_IND0) expectedContext_normalized.contexts.append(attrCtx_LVL0_IND1) expectedContext_referenceOnly = AttributeContextExpectedValue() expectedContext_referenceOnly.type = 'entity' expectedContext_referenceOnly.name = 'Employee_Resolved_referenceOnly' expectedContext_referenceOnly.definition = 'resolvedFrom/Employee' expectedContext_referenceOnly.contexts = [] attrCtx_LVL0_IND0 = AttributeContextExpectedValue() attrCtx_LVL0_IND0.type = 'entityReferenceExtends' attrCtx_LVL0_IND0.name = 'extends' attrCtx_LVL0_IND0.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly' attrCtx_LVL0_IND0.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'entity' attrCtx_LVL1_IND0.name = 'CdmEntity' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/extends' attrCtx_LVL1_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL0_IND0.contexts.append(attrCtx_LVL1_IND0) expectedContext_referenceOnly.contexts.append(attrCtx_LVL0_IND0) attrCtx_LVL0_IND1 = AttributeContextExpectedValue() attrCtx_LVL0_IND1.type = 'attributeDefinition' attrCtx_LVL0_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL0_IND1.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly' attrCtx_LVL0_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL0_IND1.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'attributeGroup' attrCtx_LVL1_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope' attrCtx_LVL1_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL1_IND0.contexts = [] attrCtx_LVL2_IND0 = AttributeContextExpectedValue() attrCtx_LVL2_IND0.type = 'attributeDefinition' attrCtx_LVL2_IND0.name = 'ID' attrCtx_LVL2_IND0.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL2_IND0.context_strings = [] attrCtx_LVL2_IND0.context_strings.append('Employee_Resolved_referenceOnly/hasAttributes/ID') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND0) attrCtx_LVL2_IND1 = AttributeContextExpectedValue() attrCtx_LVL2_IND1.type = 'attributeDefinition' attrCtx_LVL2_IND1.name = 'FullName' attrCtx_LVL2_IND1.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/FullName' attrCtx_LVL2_IND1.context_strings = [] attrCtx_LVL2_IND1.context_strings.append('Employee_Resolved_referenceOnly/hasAttributes/FullName') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND1) attrCtx_LVL2_IND2 = AttributeContextExpectedValue() attrCtx_LVL2_IND2.type = 'attributeDefinition' attrCtx_LVL2_IND2.name = 'TeamID' attrCtx_LVL2_IND2.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND2.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID' attrCtx_LVL2_IND2.contexts = [] attrCtx_LVL3_IND0 = AttributeContextExpectedValue() attrCtx_LVL3_IND0.type = 'entity' attrCtx_LVL3_IND0.name = 'Team' attrCtx_LVL3_IND0.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND0.definition = 'resolvedFrom/Team' attrCtx_LVL2_IND2.contexts.append(attrCtx_LVL3_IND0) attrCtx_LVL3_IND1 = AttributeContextExpectedValue() attrCtx_LVL3_IND1.type = 'generatedSet' attrCtx_LVL3_IND1.name = '_generatedAttributeSet' attrCtx_LVL3_IND1.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND1.contexts = [] attrCtx_LVL4_IND0 = AttributeContextExpectedValue() attrCtx_LVL4_IND0.type = 'addedAttributeExpansionTotal' attrCtx_LVL4_IND0.name = 'TeamIDTeamCount' attrCtx_LVL4_IND0.parent = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/_generatedAttributeSet' attrCtx_LVL4_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID/resolutionGuidance/countAttribute/TeamCount' attrCtx_LVL4_IND0.context_strings = [] attrCtx_LVL4_IND0.context_strings.append('Employee_Resolved_referenceOnly/hasAttributes/TeamIDTeamCount') attrCtx_LVL3_IND1.contexts.append(attrCtx_LVL4_IND0) attrCtx_LVL2_IND2.contexts.append(attrCtx_LVL3_IND1) attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND2) attrCtx_LVL0_IND1.contexts.append(attrCtx_LVL1_IND0) expectedContext_referenceOnly.contexts.append(attrCtx_LVL0_IND1) expectedContext_structured = AttributeContextExpectedValue() expectedContext_structured.type = 'entity' expectedContext_structured.name = 'Employee_Resolved_structured' expectedContext_structured.definition = 'resolvedFrom/Employee' expectedContext_structured.contexts = [] attrCtx_LVL0_IND0 = AttributeContextExpectedValue() attrCtx_LVL0_IND0.type = 'entityReferenceExtends' attrCtx_LVL0_IND0.name = 'extends' attrCtx_LVL0_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured' attrCtx_LVL0_IND0.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'entity' attrCtx_LVL1_IND0.name = 'CdmEntity' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/extends' attrCtx_LVL1_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL0_IND0.contexts.append(attrCtx_LVL1_IND0) expectedContext_structured.contexts.append(attrCtx_LVL0_IND0) attrCtx_LVL0_IND1 = AttributeContextExpectedValue() attrCtx_LVL0_IND1.type = 'attributeDefinition' attrCtx_LVL0_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL0_IND1.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured' attrCtx_LVL0_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL0_IND1.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'attributeGroup' attrCtx_LVL1_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope' attrCtx_LVL1_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL1_IND0.contexts = [] attrCtx_LVL2_IND0 = AttributeContextExpectedValue() attrCtx_LVL2_IND0.type = 'attributeDefinition' attrCtx_LVL2_IND0.name = 'ID' attrCtx_LVL2_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL2_IND0.context_strings = [] attrCtx_LVL2_IND0.context_strings.append('Employee_Resolved_structured/hasAttributes/ID') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND0) attrCtx_LVL2_IND1 = AttributeContextExpectedValue() attrCtx_LVL2_IND1.type = 'attributeDefinition' attrCtx_LVL2_IND1.name = 'FullName' attrCtx_LVL2_IND1.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/FullName' attrCtx_LVL2_IND1.context_strings = [] attrCtx_LVL2_IND1.context_strings.append('Employee_Resolved_structured/hasAttributes/FullName') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND1) attrCtx_LVL2_IND2 = AttributeContextExpectedValue() attrCtx_LVL2_IND2.type = 'attributeDefinition' attrCtx_LVL2_IND2.name = 'TeamID' attrCtx_LVL2_IND2.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND2.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID' attrCtx_LVL2_IND2.contexts = [] attrCtx_LVL3_IND0 = AttributeContextExpectedValue() attrCtx_LVL3_IND0.type = 'entity' attrCtx_LVL3_IND0.name = 'Team' attrCtx_LVL3_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND0.definition = 'resolvedFrom/Team' attrCtx_LVL3_IND0.contexts = [] attrCtx_LVL4_IND0 = AttributeContextExpectedValue() attrCtx_LVL4_IND0.type = 'entityReferenceExtends' attrCtx_LVL4_IND0.name = 'extends' attrCtx_LVL4_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team' attrCtx_LVL4_IND0.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'entity' attrCtx_LVL5_IND0.name = 'CdmEntity' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/extends' attrCtx_LVL5_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL4_IND0.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND0.contexts.append(attrCtx_LVL4_IND0) attrCtx_LVL4_IND1 = AttributeContextExpectedValue() attrCtx_LVL4_IND1.type = 'attributeDefinition' attrCtx_LVL4_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL4_IND1.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team' attrCtx_LVL4_IND1.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL4_IND1.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'attributeGroup' attrCtx_LVL5_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope' attrCtx_LVL5_IND0.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL5_IND0.contexts = [] attrCtx_LVL6_IND0 = AttributeContextExpectedValue() attrCtx_LVL6_IND0.type = 'attributeDefinition' attrCtx_LVL6_IND0.name = 'ID' attrCtx_LVL6_IND0.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL6_IND0.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL6_IND0.context_strings = [] attrCtx_LVL6_IND0.context_strings.append('Employee_Resolved_structured/hasAttributes/TeamID/members/ID') attrCtx_LVL5_IND0.contexts.append(attrCtx_LVL6_IND0) attrCtx_LVL6_IND1 = AttributeContextExpectedValue() attrCtx_LVL6_IND1.type = 'attributeDefinition' attrCtx_LVL6_IND1.name = 'Name' attrCtx_LVL6_IND1.parent = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL6_IND1.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope/members/Name' attrCtx_LVL6_IND1.context_strings = [] attrCtx_LVL6_IND1.context_strings.append('Employee_Resolved_structured/hasAttributes/TeamID/members/Name') attrCtx_LVL5_IND0.contexts.append(attrCtx_LVL6_IND1) attrCtx_LVL4_IND1.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND0.contexts.append(attrCtx_LVL4_IND1) attrCtx_LVL2_IND2.contexts.append(attrCtx_LVL3_IND0) attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND2) attrCtx_LVL0_IND1.contexts.append(attrCtx_LVL1_IND0) expectedContext_structured.contexts.append(attrCtx_LVL0_IND1) expectedContext_normalized_structured = AttributeContextExpectedValue() expectedContext_normalized_structured.type = 'entity' expectedContext_normalized_structured.name = 'Employee_Resolved_normalized_structured' expectedContext_normalized_structured.definition = 'resolvedFrom/Employee' expectedContext_normalized_structured.contexts = [] attrCtx_LVL0_IND0 = AttributeContextExpectedValue() attrCtx_LVL0_IND0.type = 'entityReferenceExtends' attrCtx_LVL0_IND0.name = 'extends' attrCtx_LVL0_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured' attrCtx_LVL0_IND0.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'entity' attrCtx_LVL1_IND0.name = 'CdmEntity' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/extends' attrCtx_LVL1_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL0_IND0.contexts.append(attrCtx_LVL1_IND0) expectedContext_normalized_structured.contexts.append(attrCtx_LVL0_IND0) attrCtx_LVL0_IND1 = AttributeContextExpectedValue() attrCtx_LVL0_IND1.type = 'attributeDefinition' attrCtx_LVL0_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL0_IND1.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured' attrCtx_LVL0_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL0_IND1.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'attributeGroup' attrCtx_LVL1_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope' attrCtx_LVL1_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL1_IND0.contexts = [] attrCtx_LVL2_IND0 = AttributeContextExpectedValue() attrCtx_LVL2_IND0.type = 'attributeDefinition' attrCtx_LVL2_IND0.name = 'TeamID' attrCtx_LVL2_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID' attrCtx_LVL2_IND0.contexts = [] attrCtx_LVL3_IND0 = AttributeContextExpectedValue() attrCtx_LVL3_IND0.type = 'entity' attrCtx_LVL3_IND0.name = 'Team' attrCtx_LVL3_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND0.definition = 'resolvedFrom/Team' attrCtx_LVL3_IND0.contexts = [] attrCtx_LVL4_IND0 = AttributeContextExpectedValue() attrCtx_LVL4_IND0.type = 'entityReferenceExtends' attrCtx_LVL4_IND0.name = 'extends' attrCtx_LVL4_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team' attrCtx_LVL4_IND0.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'entity' attrCtx_LVL5_IND0.name = 'CdmEntity' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/extends' attrCtx_LVL5_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL4_IND0.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND0.contexts.append(attrCtx_LVL4_IND0) attrCtx_LVL4_IND1 = AttributeContextExpectedValue() attrCtx_LVL4_IND1.type = 'attributeDefinition' attrCtx_LVL4_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL4_IND1.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team' attrCtx_LVL4_IND1.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL4_IND1.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'attributeGroup' attrCtx_LVL5_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope' attrCtx_LVL5_IND0.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL5_IND0.contexts = [] attrCtx_LVL6_IND0 = AttributeContextExpectedValue() attrCtx_LVL6_IND0.type = 'attributeDefinition' attrCtx_LVL6_IND0.name = 'ID' attrCtx_LVL6_IND0.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL6_IND0.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL5_IND0.contexts.append(attrCtx_LVL6_IND0) attrCtx_LVL6_IND1 = AttributeContextExpectedValue() attrCtx_LVL6_IND1.type = 'attributeDefinition' attrCtx_LVL6_IND1.name = 'Name' attrCtx_LVL6_IND1.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL6_IND1.definition = 'resolvedFrom/Team/hasAttributes/attributesAddedAtThisScope/members/Name' attrCtx_LVL5_IND0.contexts.append(attrCtx_LVL6_IND1) attrCtx_LVL4_IND1.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND0.contexts.append(attrCtx_LVL4_IND1) attrCtx_LVL2_IND0.contexts.append(attrCtx_LVL3_IND0) attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND0) attrCtx_LVL2_IND1 = AttributeContextExpectedValue() attrCtx_LVL2_IND1.type = 'attributeDefinition' attrCtx_LVL2_IND1.name = 'ID' attrCtx_LVL2_IND1.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL2_IND1.context_strings = [] attrCtx_LVL2_IND1.context_strings.append('Employee_Resolved_normalized_structured/hasAttributes/ID') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND1) attrCtx_LVL2_IND2 = AttributeContextExpectedValue() attrCtx_LVL2_IND2.type = 'attributeDefinition' attrCtx_LVL2_IND2.name = 'FullName' attrCtx_LVL2_IND2.parent = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND2.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/FullName' attrCtx_LVL2_IND2.context_strings = [] attrCtx_LVL2_IND2.context_strings.append('Employee_Resolved_normalized_structured/hasAttributes/FullName') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND2) attrCtx_LVL0_IND1.contexts.append(attrCtx_LVL1_IND0) expectedContext_normalized_structured.contexts.append(attrCtx_LVL0_IND1) expectedContext_referenceOnly_normalized = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized.type = 'entity' expectedContext_referenceOnly_normalized.name = 'Employee_Resolved_referenceOnly_normalized' expectedContext_referenceOnly_normalized.definition = 'resolvedFrom/Employee' expectedContext_referenceOnly_normalized.contexts = [] attrCtx_LVL0_IND0 = AttributeContextExpectedValue() attrCtx_LVL0_IND0.type = 'entityReferenceExtends' attrCtx_LVL0_IND0.name = 'extends' attrCtx_LVL0_IND0.parent = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized' attrCtx_LVL0_IND0.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'entity' attrCtx_LVL1_IND0.name = 'CdmEntity' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized/extends' attrCtx_LVL1_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL0_IND0.contexts.append(attrCtx_LVL1_IND0) expectedContext_referenceOnly_normalized.contexts.append(attrCtx_LVL0_IND0) attrCtx_LVL0_IND1 = AttributeContextExpectedValue() attrCtx_LVL0_IND1.type = 'attributeDefinition' attrCtx_LVL0_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL0_IND1.parent = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized' attrCtx_LVL0_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL0_IND1.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'attributeGroup' attrCtx_LVL1_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized/attributesAddedAtThisScope' attrCtx_LVL1_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL1_IND0.contexts = [] attrCtx_LVL2_IND0 = AttributeContextExpectedValue() attrCtx_LVL2_IND0.type = 'attributeDefinition' attrCtx_LVL2_IND0.name = 'TeamID' attrCtx_LVL2_IND0.parent = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID' attrCtx_LVL2_IND0.contexts = [] attrCtx_LVL3_IND0 = AttributeContextExpectedValue() attrCtx_LVL3_IND0.type = 'entity' attrCtx_LVL3_IND0.name = 'Team' attrCtx_LVL3_IND0.parent = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND0.definition = 'resolvedFrom/Team' attrCtx_LVL2_IND0.contexts.append(attrCtx_LVL3_IND0) attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND0) attrCtx_LVL2_IND1 = AttributeContextExpectedValue() attrCtx_LVL2_IND1.type = 'attributeDefinition' attrCtx_LVL2_IND1.name = 'ID' attrCtx_LVL2_IND1.parent = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL2_IND1.context_strings = [] attrCtx_LVL2_IND1.context_strings.append('Employee_Resolved_referenceOnly_normalized/hasAttributes/ID') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND1) attrCtx_LVL2_IND2 = AttributeContextExpectedValue() attrCtx_LVL2_IND2.type = 'attributeDefinition' attrCtx_LVL2_IND2.name = 'FullName' attrCtx_LVL2_IND2.parent = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND2.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/FullName' attrCtx_LVL2_IND2.context_strings = [] attrCtx_LVL2_IND2.context_strings.append('Employee_Resolved_referenceOnly_normalized/hasAttributes/FullName') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND2) attrCtx_LVL0_IND1.contexts.append(attrCtx_LVL1_IND0) expectedContext_referenceOnly_normalized.contexts.append(attrCtx_LVL0_IND1) expectedContext_referenceOnly_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_structured.type = 'entity' expectedContext_referenceOnly_structured.name = 'Employee_Resolved_referenceOnly_structured' expectedContext_referenceOnly_structured.definition = 'resolvedFrom/Employee' expectedContext_referenceOnly_structured.contexts = [] attrCtx_LVL0_IND0 = AttributeContextExpectedValue() attrCtx_LVL0_IND0.type = 'entityReferenceExtends' attrCtx_LVL0_IND0.name = 'extends' attrCtx_LVL0_IND0.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured' attrCtx_LVL0_IND0.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'entity' attrCtx_LVL1_IND0.name = 'CdmEntity' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/extends' attrCtx_LVL1_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL0_IND0.contexts.append(attrCtx_LVL1_IND0) expectedContext_referenceOnly_structured.contexts.append(attrCtx_LVL0_IND0) attrCtx_LVL0_IND1 = AttributeContextExpectedValue() attrCtx_LVL0_IND1.type = 'attributeDefinition' attrCtx_LVL0_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL0_IND1.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured' attrCtx_LVL0_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL0_IND1.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'attributeGroup' attrCtx_LVL1_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope' attrCtx_LVL1_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL1_IND0.contexts = [] attrCtx_LVL2_IND0 = AttributeContextExpectedValue() attrCtx_LVL2_IND0.type = 'attributeDefinition' attrCtx_LVL2_IND0.name = 'ID' attrCtx_LVL2_IND0.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL2_IND0.context_strings = [] attrCtx_LVL2_IND0.context_strings.append('Employee_Resolved_referenceOnly_structured/hasAttributes/ID') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND0) attrCtx_LVL2_IND1 = AttributeContextExpectedValue() attrCtx_LVL2_IND1.type = 'attributeDefinition' attrCtx_LVL2_IND1.name = 'FullName' attrCtx_LVL2_IND1.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/FullName' attrCtx_LVL2_IND1.context_strings = [] attrCtx_LVL2_IND1.context_strings.append('Employee_Resolved_referenceOnly_structured/hasAttributes/FullName') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND1) attrCtx_LVL2_IND2 = AttributeContextExpectedValue() attrCtx_LVL2_IND2.type = 'attributeDefinition' attrCtx_LVL2_IND2.name = 'TeamID' attrCtx_LVL2_IND2.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND2.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID' attrCtx_LVL2_IND2.contexts = [] attrCtx_LVL3_IND0 = AttributeContextExpectedValue() attrCtx_LVL3_IND0.type = 'entity' attrCtx_LVL3_IND0.name = 'Team' attrCtx_LVL3_IND0.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND0.definition = 'resolvedFrom/Team' attrCtx_LVL2_IND2.contexts.append(attrCtx_LVL3_IND0) attrCtx_LVL3_IND1 = AttributeContextExpectedValue() attrCtx_LVL3_IND1.type = 'generatedSet' attrCtx_LVL3_IND1.name = '_generatedAttributeSet' attrCtx_LVL3_IND1.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND1.contexts = [] attrCtx_LVL4_IND0 = AttributeContextExpectedValue() attrCtx_LVL4_IND0.type = 'generatedRound' attrCtx_LVL4_IND0.name = '_generatedAttributeRound0' attrCtx_LVL4_IND0.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/_generatedAttributeSet' attrCtx_LVL4_IND0.contexts = [] attrCtx_LVL5_IND0 = AttributeContextExpectedValue() attrCtx_LVL5_IND0.type = 'addedAttributeIdentity' attrCtx_LVL5_IND0.name = '_foreignKey' attrCtx_LVL5_IND0.parent = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/_generatedAttributeSet/_generatedAttributeRound0' attrCtx_LVL5_IND0.context_strings = [] attrCtx_LVL5_IND0.context_strings.append( 'Employee_Resolved_referenceOnly_structured/hasAttributes/TeamID/members/TeamID') attrCtx_LVL4_IND0.contexts.append(attrCtx_LVL5_IND0) attrCtx_LVL3_IND1.contexts.append(attrCtx_LVL4_IND0) attrCtx_LVL2_IND2.contexts.append(attrCtx_LVL3_IND1) attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND2) attrCtx_LVL0_IND1.contexts.append(attrCtx_LVL1_IND0) expectedContext_referenceOnly_structured.contexts.append(attrCtx_LVL0_IND1) expectedContext_referenceOnly_normalized_structured = AttributeContextExpectedValue() expectedContext_referenceOnly_normalized_structured.type = 'entity' expectedContext_referenceOnly_normalized_structured.name = 'Employee_Resolved_referenceOnly_normalized_structured' expectedContext_referenceOnly_normalized_structured.definition = 'resolvedFrom/Employee' expectedContext_referenceOnly_normalized_structured.contexts = [] attrCtx_LVL0_IND0 = AttributeContextExpectedValue() attrCtx_LVL0_IND0.type = 'entityReferenceExtends' attrCtx_LVL0_IND0.name = 'extends' attrCtx_LVL0_IND0.parent = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured' attrCtx_LVL0_IND0.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'entity' attrCtx_LVL1_IND0.name = 'CdmEntity' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured/extends' attrCtx_LVL1_IND0.definition = 'resolvedFrom/CdmEntity' attrCtx_LVL0_IND0.contexts.append(attrCtx_LVL1_IND0) expectedContext_referenceOnly_normalized_structured.contexts.append(attrCtx_LVL0_IND0) attrCtx_LVL0_IND1 = AttributeContextExpectedValue() attrCtx_LVL0_IND1.type = 'attributeDefinition' attrCtx_LVL0_IND1.name = 'attributesAddedAtThisScope' attrCtx_LVL0_IND1.parent = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured' attrCtx_LVL0_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL0_IND1.contexts = [] attrCtx_LVL1_IND0 = AttributeContextExpectedValue() attrCtx_LVL1_IND0.type = 'attributeGroup' attrCtx_LVL1_IND0.name = 'attributesAddedAtThisScope' attrCtx_LVL1_IND0.parent = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured/attributesAddedAtThisScope' attrCtx_LVL1_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope' attrCtx_LVL1_IND0.contexts = [] attrCtx_LVL2_IND0 = AttributeContextExpectedValue() attrCtx_LVL2_IND0.type = 'attributeDefinition' attrCtx_LVL2_IND0.name = 'TeamID' attrCtx_LVL2_IND0.parent = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND0.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/TeamID' attrCtx_LVL2_IND0.contexts = [] attrCtx_LVL3_IND0 = AttributeContextExpectedValue() attrCtx_LVL3_IND0.type = 'entity' attrCtx_LVL3_IND0.name = 'Team' attrCtx_LVL3_IND0.parent = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrCtx_LVL3_IND0.definition = 'resolvedFrom/Team' attrCtx_LVL2_IND0.contexts.append(attrCtx_LVL3_IND0) attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND0) attrCtx_LVL2_IND1 = AttributeContextExpectedValue() attrCtx_LVL2_IND1.type = 'attributeDefinition' attrCtx_LVL2_IND1.name = 'ID' attrCtx_LVL2_IND1.parent = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND1.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/ID' attrCtx_LVL2_IND1.context_strings = [] attrCtx_LVL2_IND1.context_strings.append( 'Employee_Resolved_referenceOnly_normalized_structured/hasAttributes/ID') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND1) attrCtx_LVL2_IND2 = AttributeContextExpectedValue() attrCtx_LVL2_IND2.type = 'attributeDefinition' attrCtx_LVL2_IND2.name = 'FullName' attrCtx_LVL2_IND2.parent = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope' attrCtx_LVL2_IND2.definition = 'resolvedFrom/Employee/hasAttributes/attributesAddedAtThisScope/members/FullName' attrCtx_LVL2_IND2.context_strings = [] attrCtx_LVL2_IND2.context_strings.append( 'Employee_Resolved_referenceOnly_normalized_structured/hasAttributes/FullName') attrCtx_LVL1_IND0.contexts.append(attrCtx_LVL2_IND2) attrCtx_LVL0_IND1.contexts.append(attrCtx_LVL1_IND0) expectedContext_referenceOnly_normalized_structured.contexts.append(attrCtx_LVL0_IND1) expected_default = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.display_name = 'ID' att.is_primary_key = True att.name = 'ID' att.source_name = 'ID' expected_default.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/FullName' att.data_format = 'String' att.display_name = 'FullName' att.name = 'FullName' att.source_name = 'FullName' expected_default.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_default/attributeContext/Employee_Resolved_default/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/_generatedAttributeSet/TeamIDTeamCount' att.data_format = 'Int32' att.name = 'TeamIDTeamCount' expected_default.append(att) expected_normalized = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.display_name = 'ID' att.is_primary_key = True att.name = 'ID' att.source_name = 'ID' expected_normalized.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_normalized/attributeContext/Employee_Resolved_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/FullName' att.data_format = 'String' att.display_name = 'FullName' att.name = 'FullName' att.source_name = 'FullName' expected_normalized.append(att) expected_referenceOnly = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.display_name = 'ID' att.is_primary_key = True att.name = 'ID' att.source_name = 'ID' expected_referenceOnly.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope/FullName' att.data_format = 'String' att.display_name = 'FullName' att.name = 'FullName' att.source_name = 'FullName' expected_referenceOnly.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly/attributeContext/Employee_Resolved_referenceOnly/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/_generatedAttributeSet/TeamIDTeamCount' att.data_format = 'Int32' att.name = 'TeamIDTeamCount' expected_referenceOnly.append(att) expected_structured = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.display_name = 'ID' att.is_primary_key = True att.name = 'ID' att.source_name = 'ID' expected_structured.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/FullName' att.data_format = 'String' att.display_name = 'FullName' att.name = 'FullName' att.source_name = 'FullName' expected_structured.append(att) attrib_group_ref = AttributeExpectedValue() attrib_group_ref.attribute_group_name = 'TeamID' attrib_group_ref.attribute_context = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrib_group_ref.members = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.name = 'ID' attrib_group_ref.members.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_structured/attributeContext/Employee_Resolved_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/Team/attributesAddedAtThisScope/attributesAddedAtThisScope/Name' att.data_format = 'String' att.name = 'Name' attrib_group_ref.members.append(att) expected_structured.append(attrib_group_ref) expected_normalized_structured = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.display_name = 'ID' att.is_primary_key = True att.name = 'ID' att.source_name = 'ID' expected_normalized_structured.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_normalized_structured/attributeContext/Employee_Resolved_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/FullName' att.data_format = 'String' att.display_name = 'FullName' att.name = 'FullName' att.source_name = 'FullName' expected_normalized_structured.append(att) expected_referenceOnly_normalized = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.display_name = 'ID' att.is_primary_key = True att.name = 'ID' att.source_name = 'ID' expected_referenceOnly_normalized.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly_normalized/attributeContext/Employee_Resolved_referenceOnly_normalized/attributesAddedAtThisScope/attributesAddedAtThisScope/FullName' att.data_format = 'String' att.display_name = 'FullName' att.name = 'FullName' att.source_name = 'FullName' expected_referenceOnly_normalized.append(att) expected_referenceOnly_structured = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.display_name = 'ID' att.is_primary_key = True att.name = 'ID' att.source_name = 'ID' expected_referenceOnly_structured.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/FullName' att.data_format = 'String' att.display_name = 'FullName' att.name = 'FullName' att.source_name = 'FullName' expected_referenceOnly_structured.append(att) attrib_group_ref = AttributeExpectedValue() attrib_group_ref.attribute_group_name = 'TeamID' attrib_group_ref.attribute_context = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID' attrib_group_ref.members = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly_structured/attributeContext/Employee_Resolved_referenceOnly_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/TeamID/_generatedAttributeSet/_generatedAttributeRound0/_foreignKey' att.data_format = 'Guid' att.description = '' att.display_name = 'TeamID' att.name = 'TeamID' att.source_name = 'TeamID' attrib_group_ref.members.append(att) expected_referenceOnly_structured.append(attrib_group_ref) expected_referenceOnly_normalized_structured = [] att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/ID' att.data_format = 'Guid' att.display_name = 'ID' att.is_primary_key = True att.name = 'ID' att.source_name = 'ID' expected_referenceOnly_normalized_structured.append(att) att = AttributeExpectedValue() att.attribute_context = 'Employee_Resolved_referenceOnly_normalized_structured/attributeContext/Employee_Resolved_referenceOnly_normalized_structured/attributesAddedAtThisScope/attributesAddedAtThisScope/FullName' att.data_format = 'String' att.display_name = 'FullName' att.name = 'FullName' att.source_name = 'FullName' expected_referenceOnly_normalized_structured.append(att) await self.run_test_with_values( test_name, entity_name, expectedContext_default, expectedContext_normalized, expectedContext_referenceOnly, expectedContext_structured, expectedContext_normalized_structured, expectedContext_referenceOnly_normalized, expectedContext_referenceOnly_structured, expectedContext_referenceOnly_normalized_structured, expected_default, expected_normalized, expected_referenceOnly, expected_structured, expected_normalized_structured, expected_referenceOnly_normalized, expected_referenceOnly_structured, expected_referenceOnly_normalized_structured )

53.979577

258

0.775946

6,566

76,651

8.622297

0.018581

0.074893

0.033914

0.027555

0.973911

0.957873

0.94625

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0.929346

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0.163064

76,651

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null

0

7

77455218233752512da621b81d7a4534b1e3f03e

3,141

py

Python

lib/models/map_modules/map_conv.py

CFM-MSG/Code_LEORN

fabea1e1ded973a4db692e51e2df442bde55f626

[ "MIT" ]

1

2022-01-31T03:23:37.000Z

lib/models/map_modules/map_conv.py

CFM-MSG/Code_LEORN

fabea1e1ded973a4db692e51e2df442bde55f626

[ "MIT" ]

null

lib/models/map_modules/map_conv.py

CFM-MSG/Code_LEORN

fabea1e1ded973a4db692e51e2df442bde55f626

[ "MIT" ]

null

from torch import nn import torch.nn.functional as F from models.map_modules import get_padded_mask_and_weight class MapConv(nn.Module): def __init__(self, cfg): super(MapConv, self).__init__() input_size = cfg.INPUT_SIZE # 512 hidden_sizes = cfg.HIDDEN_SIZES # [512, 512, 512, 512, 512, 512, 512, 512] kernel_sizes = cfg.KERNEL_SIZES # [5, 5, 5, 5, 5, 5, 5, 5] strides = cfg.STRIDES # [1, 1, 1, 1, 1, 1, 1, 1] paddings = cfg.PADDINGS # [16, 0, 0, 0, 0, 0, 0, 0] dilations = cfg.DILATIONS # [1, 1, 1, 1, 1, 1, 1, 1] self.convs = nn.ModuleList() assert len(hidden_sizes) == len(kernel_sizes) \ and len(hidden_sizes) == len(strides) \ and len(hidden_sizes) == len(paddings) \ and len(hidden_sizes) == len(dilations) channel_sizes = [input_size] + hidden_sizes for i, (k, s, p, d) in enumerate(zip(kernel_sizes, strides, paddings, dilations)): self.convs.append(nn.Conv2d(channel_sizes[i], channel_sizes[i + 1], k, s, p, d)) def forward(self, x, mask): padded_mask = mask for i, pred in enumerate(self.convs): x = F.relu(pred(x)) padded_mask, masked_weight = get_padded_mask_and_weight(padded_mask, pred) x = x * masked_weight return x # batchsize * 512 * 16 * 16 class ResMapConv(nn.Module): def __init__(self, cfg): super(ResMapConv, self).__init__() input_size = cfg.INPUT_SIZE # 512 hidden_sizes = cfg.HIDDEN_SIZES # [512, 512, 512, 512, 512, 512, 512, 512] kernel_sizes = cfg.KERNEL_SIZES # [5, 5, 5, 5, 5, 5, 5, 5] strides = cfg.STRIDES # [1, 1, 1, 1, 1, 1, 1, 1] paddings = cfg.PADDINGS # [16, 0, 0, 0, 0, 0, 0, 0] dilations = cfg.DILATIONS # [1, 1, 1, 1, 1, 1, 1, 1] self.convs = nn.ModuleList() assert len(hidden_sizes) == len(kernel_sizes) \ and len(hidden_sizes) == len(strides) \ and len(hidden_sizes) == len(paddings) \ and len(hidden_sizes) == len(dilations) channel_sizes = [input_size] + hidden_sizes for i, (k, s, p, d) in enumerate(zip(kernel_sizes, strides, paddings, dilations)): self.convs.append(nn.Conv2d(channel_sizes[i], channel_sizes[i + 1], k, s, p, d)) if 'NORM' not in cfg or cfg.NORM: self.bn_layers = nn.ModuleList( [nn.BatchNorm2d(hidden_sizes[i]) for i in range(0, len(hidden_sizes))]) self.bn_layers.append(nn.BatchNorm2d(hidden_sizes[-1])) else: self.bn_layers = None def forward(self, x, mask): padded_mask = mask if self.bn_layers is not None: x = self.bn_layers[0](x) for i, pred in enumerate(self.convs): x = pred(x) + x if self.bn_layers is not None: x = self.bn_layers[i + 1](x) x = F.relu(x) padded_mask, masked_weight = get_padded_mask_and_weight(padded_mask, pred) x = x * masked_weight return x # batchsize * 512 * 16 * 16

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3,141

71

93

44.239437

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0

0.032258

1

0.064516

false

0

0.048387

0

0.177419

0

null

0

1

0

1

0

null

0

7

620d6da422257473a3e0b00dfa88aa83620e22c0

18,933

py

Python

platform/core/tests/test_auditor/test_auditor_build_job.py

hackerwins/polyaxon

ff56a098283ca872abfbaae6ba8abba479ffa394

[ "Apache-2.0" ]

null

platform/core/tests/test_auditor/test_auditor_build_job.py

hackerwins/polyaxon

ff56a098283ca872abfbaae6ba8abba479ffa394

[ "Apache-2.0" ]

null

platform/core/tests/test_auditor/test_auditor_build_job.py

hackerwins/polyaxon

ff56a098283ca872abfbaae6ba8abba479ffa394

[ "Apache-2.0" ]

null

# pylint:disable=ungrouped-imports from unittest.mock import patch import pytest import auditor from events.registry import build_job as build_job_events from factories.factory_build_jobs import BuildJobFactory from factories.factory_projects import ProjectFactory from tests.test_auditor.utils import AuditorBaseTest @pytest.mark.auditor_mark class AuditorBuildJobTest(AuditorBaseTest): """Testing subscribed events""" EVENTS = build_job_events.EVENTS def setUp(self): super().setUp() self.build_job = BuildJobFactory(project=ProjectFactory()) self.tested_events = { build_job_events.BUILD_JOB_CREATED, build_job_events.BUILD_JOB_UPDATED, build_job_events.BUILD_JOB_STARTED, build_job_events.BUILD_JOB_STARTED_TRIGGERED, build_job_events.BUILD_JOB_DELETED, build_job_events.BUILD_JOB_DELETED_TRIGGERED, build_job_events.BUILD_JOB_STOPPED, build_job_events.BUILD_JOB_STOPPED_TRIGGERED, build_job_events.BUILD_JOB_CLEANED_TRIGGERED, build_job_events.BUILD_JOB_VIEWED, build_job_events.BUILD_JOB_ARCHIVED, build_job_events.BUILD_JOB_RESTORED, build_job_events.BUILD_JOB_BOOKMARKED, build_job_events.BUILD_JOB_UNBOOKMARKED, build_job_events.BUILD_JOB_NEW_STATUS, build_job_events.BUILD_JOB_FAILED, build_job_events.BUILD_JOB_SUCCEEDED, build_job_events.BUILD_JOB_DONE, build_job_events.BUILD_JOB_LOGS_VIEWED, build_job_events.BUILD_JOB_STATUSES_VIEWED, } @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_created(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_CREATED, instance=self.build_job) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 1 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_updated(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_UPDATED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_started(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_STARTED, instance=self.build_job) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 0 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_started_triggered(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_STARTED_TRIGGERED, instance=self.build_job, actor_id=1, actor_name='foo') assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_deleted(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_DELETED, instance=self.build_job) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 0 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_triggered_deleted(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_DELETED_TRIGGERED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_stopped(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_STOPPED, instance=self.build_job) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 0 assert notifier_record.call_count == 1 assert executor_record.call_count == 1 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_stopped_triggered(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_STOPPED_TRIGGERED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_cleaned_triggered(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_CLEANED_TRIGGERED, instance=self.build_job) assert tracker_record.call_count == 0 assert activitylogs_record.call_count == 0 assert notifier_record.call_count == 0 assert executor_record.call_count == 1 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_viewed(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_VIEWED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_archived(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_ARCHIVED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_restored(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_RESTORED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_bookmarked(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_BOOKMARKED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_unbookmarked(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_UNBOOKMARKED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_new_status(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_NEW_STATUS, instance=self.build_job) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 0 assert notifier_record.call_count == 0 assert executor_record.call_count == 1 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_failed(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_FAILED, instance=self.build_job) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 0 assert notifier_record.call_count == 1 assert executor_record.call_count == 1 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_succeeded(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_SUCCEEDED, instance=self.build_job) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 0 assert notifier_record.call_count == 1 assert executor_record.call_count == 1 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_done(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_DONE, instance=self.build_job) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 0 assert notifier_record.call_count == 0 assert executor_record.call_count == 1 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_logs_viewed_triggered(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_LOGS_VIEWED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 @patch('executor.executor_service.ExecutorService.record_event') @patch('notifier.service.NotifierService.record_event') @patch('tracker.service.TrackerService.record_event') @patch('activitylogs.service.ActivityLogService.record_event') def test_build_job_statuses_viewed_triggered(self, activitylogs_record, tracker_record, notifier_record, executor_record): auditor.record(event_type=build_job_events.BUILD_JOB_STATUSES_VIEWED, instance=self.build_job, actor_name='foo', actor_id=1) assert tracker_record.call_count == 1 assert activitylogs_record.call_count == 1 assert notifier_record.call_count == 0 assert executor_record.call_count == 0 del AuditorBaseTest

46.178049

79

0.615116

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6.027976

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0.1092

0.059696

0.944035

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0.873237

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0

null

0

1

0

1

0

null

0

7

6560aaad30544d619056a21227a12d1b8fb2982a

5,552

py

Python

xwp/spectral_1d.py

s-sajid-ali/xray_wave_propagators

2540f0d4009f202d7dcd2b994b598fa54c151359

[ "MIT" ]

4

2019-01-12T22:43:03.000Z

2021-05-09T17:32:45.000Z

xwp/spectral_1d.py

s-sajid-ali/xray_wave_propagators

2540f0d4009f202d7dcd2b994b598fa54c151359

[ "MIT" ]

null

xwp/spectral_1d.py

s-sajid-ali/xray_wave_propagators

2540f0d4009f202d7dcd2b994b598fa54c151359

[ "MIT" ]

null

#1D versions of propagators import numpy as np __all__ = ['propTF', 'prop1FT', 'propFF', 'propIR'] ''' Propogation using the Transfer function method. Inputs - u : profile of the beam at the input plane. step : is the sampling step size at the input plane. L1 : side length of the support. wavel : the wavelength of the light z : the propogation distance fft_object : (not implemented) to pass an FFTW object for evaluation of the FFT Outputs - u : beam profile at the output plane L1 : the side length of the support at the output plane. ''' try: import numexpr as ne def propTF(u,step,L1,wavel,z,fft_object = None) : N = np.shape(u)[0] pi = np.pi F = np.fft.fftfreq(N,step) u = np.fft.fft(u) u = ne.evaluate('exp(-1j*(2*pi*z/wavel)*sqrt(1-wavel**2*(F**2)))*u') u = np.fft.ifft(u) return u,L1 except: def propTF(u,step,L1,wavel,z,fft_object = None) : N = np.shape(u)[0] pi = np.pi F = np.fft.fftfreq(N,step) u = np.fft.fft(u) u = np.exp(-1j*(2*pi*z/wavel)*np.sqrt(1-wavel**2*(F**2)))*u u = np.fft.ifft(u) return u,L1 ''' Propogation using the Single Fourier Transform approach. Input convention as above. Inputs - u : profile of the beam at the input plane. step : is the sampling step size at the input plane. L1 : side length of the support. wavel : the wavelength of the light z :the propogation distance fft_object : (not implemented) to pass an FFTW object for evaluation of the FFT Outputs - u : beam profile at the output plane L_out : the side length of the support at the output plane. ''' try: import numexpr as ne def prop1FT(u,step,L1,wavel,z,fft_object = None): N = np.shape(u)[0] k = 2*np.pi/wavel x = np.linspace(-L1/2.0,L1/2.0,N) L_out = wavel*z/step step2 = wavel*z/L1 pi = np.pi #Kenan's approach f = np.fft.fftfreq(N,d=step) f = np.fft.fftshift(f) #c = np.exp((-1j*z*2*np.pi/wavel)*np.sqrt(1+wavel**2*(f**2))) #c = np.exp((-1j*2*np.pi/wavel)*np.sqrt(x**2+z**2)) #u = u*c u = ne.evaluate('exp(1j*pi/(wavel*z)*(x**2))*u') u = np.fft.fft(u)*step u = np.fft.fftshift(u) #x2 = np.linspace(-L_out/2.0,L_out/2.0,N) #u = ne.evaluate('exp((-1j*2*pi/wavel)*sqrt(x2**2+z**2))*u') u = ne.evaluate('u*(sqrt(1/(1j*wavel*z)))') return u,L_out except: def prop1FT(u,step,L1,wavel,z,fft_object = None): N = np.shape(u)[0] k = 2*np.pi/wavel x = np.linspace(-L1/2.0,L1/2.0,N) L_out = wavel*z/step step2 = wavel*z/L1 pi = np.pi #Kenan's approach f = np.fft.fftfreq(N,d=step) f = np.fft.fftshift(f) #c = np.exp((-1j*z*2*np.pi/wavel)*np.sqrt(1+wavel**2*(f**2))) #c = np.exp((-1j*2*np.pi/wavel)*np.sqrt(x**2+z**2)) #u = u*c u = np.exp(1j*pi/(wavel*z)*(x**2))*u u = np.fft.fft(u)*step u = np.fft.fftshift(u) #x2 = np.linspace(-L_out/2.0,L_out/2.0,N) #u = ne.evaluate('exp((-1j*2*pi/wavel)*sqrt(x2**2+z**2))*u') u = u*(np.sqrt(1/(1j*wavel*z))) return u,L_out ''' Fraunhofer propogation. Inputs - u : profile of the beam at the input plane. step : is the sampling step size at the input plane. L1 : side length of the support. wavel : the wavelength of the light z :the propogation distance fft_object : (not implemented) to pass an FFTW object for evaluation of the FFT Outputs - u : beam profile at the output plane L_out : the side length of the support at the output plane. ''' def propFF(u,step,L1,wavel,z,fft_object = None): N = np.shape(u)[0] k = 2*np.pi/wavel L_out = wavel*z/step step2 = wavel*z/L1 n = N #number of samples x2 = np.linspace(-L_out/2.0,L_out/2.0,N) #c = ne.evaluate('exp(((1j*k)/(2*z))*(x2**2))') u = np.fft.fft(u)*step u = np.fft.fftshift(u) #u = ne.evaluate('c*u') u = u*np.sqrt(1/(1j*wavel*z)) return u,L_out ''' Warning : use is now Deprecated ! Propogation using the Impulse Response function. The convention of shiftinng a function in realspace before performing the fourier transform which is used in the reference is followed here. Input convention as above. Use is deprecated since the implementation of 1FT for ranges that are too large for TF but too small for FF. ''' try: import numexpr as ne def propIR(u,step,L,wavel,z,fft_object = None): N = np.shape(u)[0] k = 2*np.pi/wavel x = np.linspace(-L/2.0,L/2.0,N) h = ne.evaluate('1/sqrt(1j*wavel*z)*exp(((1j*k)/(2*z))*(x**2))') h = np.fft.fft(np.fft.fftshift(h))*step u = np.fft.fft(u) #u *= h u = ne.evaluate('h * u') u = np.fft.ifft(u) return u,L except: def propIR(u,step,L,wavel,z,fft_object = None): N = np.shape(u)[0] k = 2*np.pi/wavel x = np.linspace(-L/2.0,L/2.0,N) #h = ne.evaluate('(exp(1j*k*z)/(1j*wavel*z))*exp(((1j*k)/(2*z))*(x**2))') #h = np.exp(1j*k*z)*np.exp(((1j*k)/(2*z))*(x**2)) h = np.sqrt(1/(1j*wavel*z))*np.exp(((1j*k)/(2*z))*(x**2)) h = np.fft.fft(np.fft.fftshift(h))*step u = np.fft.fft(u) u *= h #u = ne.evaluate('h * u') u = np.fft.ifft(u) return u,L

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null

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7

656e1a531742b980122139e358de7f967d633c43

2,833

py

Python

tests/data/nextbus/multi_predict_two.py

tylernorth/public-transit

e2430078557adf9d2ad03d794ea551a7b06ce145

[ "BSD-2-Clause-FreeBSD" ]

null

tests/data/nextbus/multi_predict_two.py

tylernorth/public-transit

e2430078557adf9d2ad03d794ea551a7b06ce145

[ "BSD-2-Clause-FreeBSD" ]

null

tests/data/nextbus/multi_predict_two.py

tylernorth/public-transit

e2430078557adf9d2ad03d794ea551a7b06ce145

[ "BSD-2-Clause-FreeBSD" ]

3

2017-03-17T11:54:09.000Z

2022-01-21T05:07:16.000Z

text = '''<?xml version="1.0" encoding="utf-8" ?> <body copyright="All data copyright San Francisco Muni 2015."> <predictions agencyTitle="San Francisco Muni" routeTitle="38-Geary" routeTag="38" stopTitle="43rd Ave & Point Lobos Ave" stopTag="13568"> <direction title="Inbound to Downtown"> <prediction epochTime="1434139707528" seconds="1625" minutes="27" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6241" block="3806" tripTag="6629317" /> <prediction epochTime="1434140667528" seconds="2585" minutes="43" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6406" block="3808" tripTag="6629319" /> <prediction epochTime="1434141627528" seconds="3545" minutes="59" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6420" block="3811" tripTag="6629321" /> <prediction epochTime="1434142587528" seconds="4505" minutes="75" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6292" block="3843" tripTag="6629323" /> <prediction epochTime="1434143487528" seconds="5405" minutes="90" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6283" block="3813" tripTag="6629325" /> </direction> <message text="Go to sfmta.com 4 Email/Text Alerts." priority="Low"/> <message text="Discount cash fare increase 7/1. Info at sfmta.com or 3-1-1." priority="Low"/> <message text="We're on Twitter: @sfmta_muni" priority="Low"/> </predictions> <predictions agencyTitle="San Francisco Muni" routeTitle="38-Geary" routeTag="38" stopTitle="43rd Ave & Clement St" stopTag="13567"> <direction title="Inbound to Downtown"> <prediction epochTime="1434139691349" seconds="1608" minutes="26" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6241" block="3806" tripTag="6629317" /> <prediction epochTime="1434140651349" seconds="2568" minutes="42" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6406" block="3808" tripTag="6629319" /> <prediction epochTime="1434141611349" seconds="3528" minutes="58" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6420" block="3811" tripTag="6629321" /> <prediction epochTime="1434142571349" seconds="4488" minutes="74" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6292" block="3843" tripTag="6629323" /> <prediction epochTime="1434143471349" seconds="5388" minutes="89" isDeparture="false" affectedByLayover="true" dirTag="38___I_F10" vehicle="6283" block="3813" tripTag="6629325" /> </direction> <message text="Go to sfmta.com 4 Email/Text Alerts." priority="Low"/> <message text="Discount cash fare increase 7/1. Info at sfmta.com or 3-1-1." priority="Low"/> <message text="We're on Twitter: @sfmta_muni" priority="Low"/> </predictions> </body> '''

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1

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null

0

10

65a2f412793ec040dc1157cf255558bf6e1956fe

2,921

py

Python

twitter_api_handler/MapStatusToList.py

DanielFrc/twitter-stream

28cb239742d851cb1ca8675f386ce206412c32ab

[ "MIT" ]

null

twitter_api_handler/MapStatusToList.py

DanielFrc/twitter-stream

28cb239742d851cb1ca8675f386ce206412c32ab

[ "MIT" ]

null

twitter_api_handler/MapStatusToList.py

DanielFrc/twitter-stream

28cb239742d851cb1ca8675f386ce206412c32ab

[ "MIT" ]

null

from util import constants as constants class MapStatusToList: def map_tweepy_list (self, tweets): """ Function to map status object to a simple list (csv compatible) Params: tweets(obj): List of tweets in raw format Return: tweets_list(Array): Array of tweets in a clean format. """ tweets_lists = [[tweet.created_at, tweet.id, tweet.id_str, tweet.truncated, tweet.text, str(constants.TRACKS), tweet.source, tweet.source_url, tweet.in_reply_to_status_id, tweet.in_reply_to_status_id_str, tweet.in_reply_to_user_id, tweet.in_reply_to_user_id_str, tweet.in_reply_to_screen_name, tweet.user.screen_name, tweet.user.location, tweet.geo, tweet.coordinates, tweet.place, tweet.contributors, tweet.is_quote_status, tweet.retweet_count, tweet.favorite_count, tweet.favorited, tweet.retweeted, tweet.lang ] for tweet in tweets] return tweets_lists def map_tweepy_array (self, tweet): """ Function to map status object to a simple list (csv compatible) Params: tweet(str): List of tweets in raw format Return: tweets_list(Array): Array of tweets in a clean format. """ new_tweet = [tweet.created_at, tweet.id, tweet.id_str, tweet.truncated, tweet.text, str(constants.TRACKS), tweet.source, tweet.source_url, tweet.in_reply_to_status_id, tweet.in_reply_to_status_id_str, tweet.in_reply_to_user_id, tweet.in_reply_to_user_id_str, tweet.in_reply_to_screen_name, tweet.user.screen_name, tweet.user.location, tweet.geo, tweet.coordinates, tweet.place, tweet.contributors, tweet.is_quote_status, tweet.retweet_count, tweet.favorite_count, tweet.favorited, tweet.retweeted, tweet.lang ] return new_tweet

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null

0

8

02b468f51a88bb9d1a55bb8fee9114244dc05a33

2,270

py

Python

tests/e2e/test_requests_custom.py

CarlosAMolina/requests

47972fc7c0a1f786a90900222fdadae24c0c0d51

[ "MIT" ]

1

2020-11-11T11:17:48.000Z

tests/e2e/test_requests_custom.py

CarlosAMolina/requests

47972fc7c0a1f786a90900222fdadae24c0c0d51

[ "MIT" ]

3

2021-04-27T20:13:41.000Z

2021-04-27T20:13:46.000Z

tests/e2e/test_requests_custom.py

CarlosAMolina/requests

47972fc7c0a1f786a90900222fdadae24c0c0d51

[ "MIT" ]

null

import unittest from requests import exceptions from requests_custom.requests_custom import RequestsCustom class TestRequestsCustom(unittest.TestCase): """ .. _URLs information https://httpstat.us/. """ def test_get_url_with_a_correct_response_works(self): requests_custom = RequestsCustom(debug_simple=True).get_requests() URL = "https://duckduckgo.com" response = requests_custom.get(URL) self.assertEqual(200, response.status_code) def test_get_url_with_a_timeout_response_raises_an_exception(self): requests_custom = RequestsCustom(debug_simple=True) requests_custom.RETRY_ATTEMPTS = 1 requests_custom.BACKOFF_FACTOR = 0 requests_custom._log_backoff_factor() requests_custom = requests_custom.get_requests() URL = "https://httpstat.us/408" try: requests_custom.get(URL) raise Exception("Expected RetryError exception not raised") except exceptions.RetryError: self.assertTrue(True) def test_get_url_with_a_delayed_response_fails(self): requests_custom = RequestsCustom(debug_simple=True) requests_custom.RETRY_ATTEMPTS = 0 requests_custom.BACKOFF_FACTOR = 0 requests_custom.TIMEOUT_DEFAULT = 0.1 requests_custom._log_backoff_factor() requests_custom = requests_custom.get_requests() URL = "https://httpstat.us/200?sleep={miliseconds}".format(miliseconds=200) try: requests_custom.get(URL) raise Exception("Expected RetryError exception not raised") except exceptions.ConnectionError: self.assertTrue(True) def test_get_url_with_a_delayed_response_works(self): requests_custom = RequestsCustom(debug_simple=True) requests_custom.RETRY_ATTEMPTS = 0 requests_custom.BACKOFF_FACTOR = 0 requests_custom.TIMEOUT_DEFAULT = 1 requests_custom._log_backoff_factor() requests_custom = requests_custom.get_requests() URL = "https://httpstat.us/200?sleep={miliseconds}".format(miliseconds=100) response = requests_custom.get(URL) self.assertEqual(200, response.status_code) if __name__ == "__main__": unittest.main()

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null

1

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null

0

7

02d04b4d0db5df29cdba9b5b024159dbc904300f

107

py

Python

examples/Movie-Lens/best_params/__init__.py

faizanahemad/Hybrid-Weighted-Embedding-Recommender

904a27c4b0126935735aee689408b2b6acf4af9a

[ "MIT" ]

12

2019-11-29T00:06:01.000Z

2021-07-01T10:43:58.000Z

examples/Movie-Lens/best_params/__init__.py

kiminh/Hybrid-Weighted-Embedding-Recommender

457c4f13521aefa70476947c5849e85482abc3d4

[ "MIT" ]

10

2020-03-31T09:54:00.000Z

2022-03-12T00:05:21.000Z

examples/Movie-Lens/best_params/__init__.py

kiminh/Hybrid-Weighted-Embedding-Recommender

457c4f13521aefa70476947c5849e85482abc3d4

[ "MIT" ]

2

2019-12-10T04:11:32.000Z

2020-10-29T02:57:01.000Z

from .gcn_ncf_100K import params as params_gcn_ncf_100K from .gcn_ncf_1M import params as params_gcn_ncf_1M

53.5

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1

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null

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1

0

1

0

7

f30551b6ca496bbf75fe2f996b72a43e3be33181

39,790

bzl

Python

3rdparty/target_file.bzl

Jonathan-2287/bazel-deps

514c479c1afd3c4c73c6181f977e1066d65ceb8f

[ "MIT" ]

235

2016-07-26T02:10:16.000Z

2022-03-31T06:23:15.000Z

3rdparty/target_file.bzl

Jonathan-2287/bazel-deps

514c479c1afd3c4c73c6181f977e1066d65ceb8f

[ "MIT" ]

251

2016-06-23T03:53:26.000Z

2022-03-24T18:18:19.000Z

3rdparty/target_file.bzl

Jonathan-2287/bazel-deps

514c479c1afd3c4c73c6181f977e1066d65ceb8f

[ "MIT" ]

107

2016-08-22T06:12:57.000Z

2022-02-01T19:18:25.000Z

# Do not edit. bazel-deps autogenerates this file from. _JAVA_LIBRARY_TEMPLATE = """ java_library( name = "{name}", exports = [ {exports} ], runtime_deps = [ {runtime_deps} ], visibility = [ "{visibility}" ] )\n""" _SCALA_IMPORT_TEMPLATE = """ scala_import( name = "{name}", exports = [ {exports} ], jars = [ {jars} ], runtime_deps = [ {runtime_deps} ], visibility = [ "{visibility}" ] ) """ _SCALA_LIBRARY_TEMPLATE = """ scala_library( name = "{name}", exports = [ {exports} ], runtime_deps = [ {runtime_deps} ], visibility = [ "{visibility}" ] ) """ def _build_external_workspace_from_opts_impl(ctx): build_header = ctx.attr.build_header separator = ctx.attr.separator target_configs = ctx.attr.target_configs result_dict = {} for key, cfg in target_configs.items(): build_file_to_target_name = key.split(":") build_file = build_file_to_target_name[0] target_name = build_file_to_target_name[1] if build_file not in result_dict: result_dict[build_file] = [] result_dict[build_file].append(cfg) for key, file_entries in result_dict.items(): build_file_contents = build_header + '\n\n' for build_target in file_entries: entry_map = {} for entry in build_target: elements = entry.split(separator) build_entry_key = elements[0] if elements[1] == "L": entry_map[build_entry_key] = [e for e in elements[2::] if len(e) > 0] elif elements[1] == "B": entry_map[build_entry_key] = (elements[2] == "true" or elements[2] == "True") else: entry_map[build_entry_key] = elements[2] exports_str = "" for e in entry_map.get("exports", []): exports_str += "\"" + e + "\",\n" jars_str = "" for e in entry_map.get("jars", []): jars_str += "\"" + e + "\",\n" runtime_deps_str = "" for e in entry_map.get("runtimeDeps", []): runtime_deps_str += "\"" + e + "\",\n" name = entry_map["name"].split(":")[1] if entry_map["lang"] == "java": build_file_contents += _JAVA_LIBRARY_TEMPLATE.format(name = name, exports=exports_str, runtime_deps=runtime_deps_str, visibility=entry_map["visibility"]) elif entry_map["lang"].startswith("scala") and entry_map["kind"] == "import": build_file_contents += _SCALA_IMPORT_TEMPLATE.format(name = name, exports=exports_str, jars=jars_str, runtime_deps=runtime_deps_str, visibility=entry_map["visibility"]) elif entry_map["lang"].startswith("scala") and entry_map["kind"] == "library": build_file_contents += _SCALA_LIBRARY_TEMPLATE.format(name = name, exports=exports_str, runtime_deps=runtime_deps_str, visibility=entry_map["visibility"]) else: print(entry_map) ctx.file(ctx.path(key + "/BUILD"), build_file_contents, False) return None build_external_workspace_from_opts = repository_rule( attrs = { "target_configs": attr.string_list_dict(mandatory = True), "separator": attr.string(mandatory = True), "build_header": attr.string(mandatory = True), }, implementation = _build_external_workspace_from_opts_impl ) def build_header(): return """load("@io_bazel_rules_scala//scala:scala_import.bzl", "scala_import") load("@io_bazel_rules_scala//scala:scala.bzl", "scala_library")""" def list_target_data_separator(): return "|||" def list_target_data(): return { "3rdparty/jvm/com/fasterxml/jackson/core:jackson_annotations": ["lang||||||java","name||||||//3rdparty/jvm/com/fasterxml/jackson/core:jackson_annotations","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/com/fasterxml/jackson/core/jackson_annotations","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/com/fasterxml/jackson/core:jackson_core": ["lang||||||java","name||||||//3rdparty/jvm/com/fasterxml/jackson/core:jackson_core","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/com/fasterxml/jackson/core/jackson_core","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/com/fasterxml/jackson/core:jackson_databind": ["lang||||||java","name||||||//3rdparty/jvm/com/fasterxml/jackson/core:jackson_databind","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/com/fasterxml/jackson/core/jackson_databind","runtimeDeps|||L|||//3rdparty/jvm/com/fasterxml/jackson/core:jackson_annotations|||//3rdparty/jvm/com/fasterxml/jackson/core:jackson_core","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/com/fasterxml/jackson/dataformat:jackson_dataformat_yaml": ["lang||||||java","name||||||//3rdparty/jvm/com/fasterxml/jackson/dataformat:jackson_dataformat_yaml","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/com/fasterxml/jackson/dataformat/jackson_dataformat_yaml","runtimeDeps|||L|||//3rdparty/jvm/com/fasterxml/jackson/core:jackson_core|||//3rdparty/jvm/com/fasterxml/jackson/core:jackson_databind|||//3rdparty/jvm/org/yaml:snakeyaml","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/com/google/guava:guava": ["lang||||||java","name||||||//3rdparty/jvm/com/google/guava:guava","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/com/google/guava/guava","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/commons_codec:commons_codec": ["lang||||||java","name||||||//3rdparty/jvm/commons_codec:commons_codec","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/commons_codec/commons_codec","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/javax/annotation:jsr250_api": ["lang||||||java","name||||||//3rdparty/jvm/javax/annotation:jsr250_api","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/javax/annotation/jsr250_api","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/javax/enterprise:cdi_api": ["lang||||||java","name||||||//3rdparty/jvm/javax/enterprise:cdi_api","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/javax/enterprise/cdi_api","runtimeDeps|||L|||//3rdparty/jvm/javax/annotation:jsr250_api|||//3rdparty/jvm/javax/inject:javax_inject","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/javax/inject:javax_inject": ["lang||||||java","name||||||//3rdparty/jvm/javax/inject:javax_inject","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/javax/inject/javax_inject","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/commons:commons_lang3": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/commons:commons_lang3","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/commons/commons_lang3","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/httpcomponents:httpclient": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/httpcomponents:httpclient","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/httpcomponents/httpclient","runtimeDeps|||L|||//3rdparty/jvm/org/apache/httpcomponents:httpcore|||//3rdparty/jvm/commons_codec:commons_codec","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/httpcomponents:httpcore": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/httpcomponents:httpcore","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/httpcomponents/httpcore","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/maven:maven_aether_provider": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/maven:maven_aether_provider","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/maven/maven_aether_provider","runtimeDeps|||L|||//3rdparty/jvm/org/apache/maven:maven_model|||//3rdparty/jvm/org/apache/commons:commons_lang3|||//3rdparty/jvm/org/codehaus/plexus:plexus_component_annotations|||//3rdparty/jvm/org/eclipse/aether:aether_spi|||//3rdparty/jvm/org/apache/maven:maven_model_builder|||//3rdparty/jvm/org/codehaus/plexus:plexus_utils|||//3rdparty/jvm/org/eclipse/aether:aether_util|||//3rdparty/jvm/org/eclipse/aether:aether_api|||//3rdparty/jvm/org/eclipse/aether:aether_impl|||//3rdparty/jvm/org/apache/maven:maven_repository_metadata","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/maven:maven_artifact": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/maven:maven_artifact","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/maven/maven_artifact","runtimeDeps|||L|||//3rdparty/jvm/org/codehaus/plexus:plexus_utils|||//3rdparty/jvm/org/apache/commons:commons_lang3","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/maven:maven_builder_support": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/maven:maven_builder_support","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/maven/maven_builder_support","runtimeDeps|||L|||//3rdparty/jvm/org/codehaus/plexus:plexus_utils|||//3rdparty/jvm/org/apache/commons:commons_lang3","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/maven:maven_model": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/maven:maven_model","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/maven/maven_model","runtimeDeps|||L|||//3rdparty/jvm/org/codehaus/plexus:plexus_utils|||//3rdparty/jvm/org/apache/commons:commons_lang3","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/maven:maven_model_builder": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/maven:maven_model_builder","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/maven/maven_model_builder","runtimeDeps|||L|||//3rdparty/jvm/org/apache/maven:maven_model|||//3rdparty/jvm/org/apache/commons:commons_lang3|||//3rdparty/jvm/org/apache/maven:maven_builder_support|||//3rdparty/jvm/com/google/guava:guava|||//3rdparty/jvm/org/codehaus/plexus:plexus_component_annotations|||//3rdparty/jvm/org/codehaus/plexus:plexus_utils|||//3rdparty/jvm/org/apache/maven:maven_artifact|||//3rdparty/jvm/org/codehaus/plexus:plexus_interpolation","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/maven:maven_repository_metadata": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/maven:maven_repository_metadata","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/maven/maven_repository_metadata","runtimeDeps|||L|||//3rdparty/jvm/org/codehaus/plexus:plexus_utils","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/maven:maven_settings": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/maven:maven_settings","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/maven/maven_settings","runtimeDeps|||L|||//3rdparty/jvm/org/codehaus/plexus:plexus_utils","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/apache/maven:maven_settings_builder": ["lang||||||java","name||||||//3rdparty/jvm/org/apache/maven:maven_settings_builder","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/apache/maven/maven_settings_builder","runtimeDeps|||L|||//3rdparty/jvm/org/apache/commons:commons_lang3|||//3rdparty/jvm/org/apache/maven:maven_builder_support|||//3rdparty/jvm/org/sonatype/plexus:plexus_sec_dispatcher|||//3rdparty/jvm/org/codehaus/plexus:plexus_component_annotations|||//3rdparty/jvm/org/codehaus/plexus:plexus_utils|||//3rdparty/jvm/org/codehaus/plexus:plexus_interpolation|||//3rdparty/jvm/org/apache/maven:maven_settings","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/codehaus/plexus:plexus_classworlds": ["lang||||||java","name||||||//3rdparty/jvm/org/codehaus/plexus:plexus_classworlds","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/codehaus/plexus/plexus_classworlds","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/codehaus/plexus:plexus_component_annotations": ["lang||||||java","name||||||//3rdparty/jvm/org/codehaus/plexus:plexus_component_annotations","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/codehaus/plexus/plexus_component_annotations","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/codehaus/plexus:plexus_interpolation": ["lang||||||java","name||||||//3rdparty/jvm/org/codehaus/plexus:plexus_interpolation","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/codehaus/plexus/plexus_interpolation","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/codehaus/plexus:plexus_utils": ["lang||||||java","name||||||//3rdparty/jvm/org/codehaus/plexus:plexus_utils","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/codehaus/plexus/plexus_utils","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/aether:aether_api": ["lang||||||java","name||||||//3rdparty/jvm/org/eclipse/aether:aether_api","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/eclipse/aether/aether_api","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/aether:aether_connector_basic": ["lang||||||java","name||||||//3rdparty/jvm/org/eclipse/aether:aether_connector_basic","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/eclipse/aether/aether_connector_basic","runtimeDeps|||L|||//3rdparty/jvm/org/eclipse/aether:aether_api|||//3rdparty/jvm/org/eclipse/aether:aether_spi|||//3rdparty/jvm/org/eclipse/aether:aether_util","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/aether:aether_impl": ["lang||||||java","name||||||//3rdparty/jvm/org/eclipse/aether:aether_impl","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/eclipse/aether/aether_impl","runtimeDeps|||L|||//3rdparty/jvm/org/eclipse/aether:aether_api|||//3rdparty/jvm/org/eclipse/aether:aether_spi|||//3rdparty/jvm/org/eclipse/aether:aether_util","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/aether:aether_spi": ["lang||||||java","name||||||//3rdparty/jvm/org/eclipse/aether:aether_spi","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/eclipse/aether/aether_spi","runtimeDeps|||L|||//3rdparty/jvm/org/eclipse/aether:aether_api","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/aether:aether_transport_file": ["lang||||||java","name||||||//3rdparty/jvm/org/eclipse/aether:aether_transport_file","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/eclipse/aether/aether_transport_file","runtimeDeps|||L|||//3rdparty/jvm/org/eclipse/aether:aether_api|||//3rdparty/jvm/org/eclipse/aether:aether_spi|||//3rdparty/jvm/org/eclipse/aether:aether_util","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/aether:aether_transport_http": ["lang||||||java","name||||||//3rdparty/jvm/org/eclipse/aether:aether_transport_http","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/eclipse/aether/aether_transport_http","runtimeDeps|||L|||//3rdparty/jvm/org/eclipse/aether:aether_spi|||//3rdparty/jvm/org/eclipse/aether:aether_util|||//3rdparty/jvm/org/eclipse/aether:aether_api|||//3rdparty/jvm/org/apache/httpcomponents:httpclient|||//3rdparty/jvm/org/slf4j:jcl_over_slf4j","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/aether:aether_util": ["lang||||||java","name||||||//3rdparty/jvm/org/eclipse/aether:aether_util","visibility||||||//visibility:public","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/eclipse/aether/aether_util","runtimeDeps|||L|||//3rdparty/jvm/org/eclipse/aether:aether_api","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/sisu:org_eclipse_sisu_inject": ["lang||||||java","name||||||//3rdparty/jvm/org/eclipse/sisu:org_eclipse_sisu_inject","visibility||||||//3rdparty/jvm:__subpackages__","kind||||||library","deps|||L|||","jars|||L|||","sources|||L|||","exports|||L|||//external:jar/org/eclipse/sisu/org_eclipse_sisu_inject","runtimeDeps|||L|||","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/eclipse/sisu:org_eclipse_sisu_plexus": 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"3rdparty/jvm/org/typelevel:macro_compat": ["lang||||||scala:2.11.8","name||||||//3rdparty/jvm/org/typelevel:macro_compat","visibility||||||//visibility:public","kind||||||import","deps|||L|||","jars|||L|||//external:jar/org/typelevel/macro_compat_2_11","sources|||L|||","exports|||L|||","runtimeDeps|||L|||//3rdparty/jvm/org/scala_lang:scala_library","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"], "3rdparty/jvm/org/typelevel:paiges_core": ["lang||||||scala:2.11.8","name||||||//3rdparty/jvm/org/typelevel:paiges_core","visibility||||||//visibility:public","kind||||||import","deps|||L|||","jars|||L|||//external:jar/org/typelevel/paiges_core_2_11","sources|||L|||","exports|||L|||","runtimeDeps|||L|||//3rdparty/jvm/org/scala_lang:scala_library","processorClasses|||L|||","generatesApi|||B|||false","licenses|||L|||","generateNeverlink|||B|||false"] } def build_external_workspace(name): return build_external_workspace_from_opts(name = name, target_configs = list_target_data(), separator = list_target_data_separator(), build_header = build_header())

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f30d1c1344197ed61ecfb7de4c673a791a992e5f

66

py

Python

custom_addons/sales_practice/models/__init__.py

MonwarAdeeb/Bista_Solutions

d261e31f21ff03b2cc82b0c26d680036dca6d799

[ "MIT" ]

null

custom_addons/sales_practice/models/__init__.py

MonwarAdeeb/Bista_Solutions

d261e31f21ff03b2cc82b0c26d680036dca6d799

[ "MIT" ]

null

custom_addons/sales_practice/models/__init__.py

MonwarAdeeb/Bista_Solutions

d261e31f21ff03b2cc82b0c26d680036dca6d799

[ "MIT" ]

null

from . import sales_practice from . import sales_practice_inherit

22

36

0.848485

9

66

5.888889

0.555556

0.377358

0.566038

0.867925

0

0.121212

66

2

37

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0.913793

0

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true

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1

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1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

b83b6af738618f96f45710588f3cb85d0c2e4fef

92

py

Python

nnutil/visual/__init__.py

aroig/nnutil

88df41ee89f592a28c1661ee8837dd8e8ca42cf3

[ "BSD-3-Clause" ]

null

nnutil/visual/__init__.py

aroig/nnutil

88df41ee89f592a28c1661ee8837dd8e8ca42cf3

[ "BSD-3-Clause" ]

null

nnutil/visual/__init__.py

aroig/nnutil

88df41ee89f592a28c1661ee8837dd8e8ca42cf3

[ "BSD-3-Clause" ]

null

from .plot_sample import * # For backwards compatibility from ..util.print_sample import *

18.4

33

0.782609

12

92

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null

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7

b867d31001a9a733b1572df3f9738ca8ee119eae

27,657

py

Python

tests/test_models/test_heads.py

kartikwar/Swin-Transformer-Semantic-Segmentation

d9b33fbd30d8572a8806754a86c785b6342c0b2a

[ "Apache-2.0" ]

7

2021-05-22T09:02:06.000Z

2021-09-25T16:48:00.000Z

tests/test_models/test_heads.py

kartikwar/Swin-Transformer-Semantic-Segmentation

d9b33fbd30d8572a8806754a86c785b6342c0b2a

[ "Apache-2.0" ]

null

tests/test_models/test_heads.py

kartikwar/Swin-Transformer-Semantic-Segmentation

d9b33fbd30d8572a8806754a86c785b6342c0b2a

[ "Apache-2.0" ]

null

from unittest.mock import patch import pytest import torch from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule from mmcv.utils import ConfigDict from mmcv.utils.parrots_wrapper import SyncBatchNorm from mmseg.models.decode_heads import (ANNHead, APCHead, ASPPHead, CCHead, DAHead, DepthwiseSeparableASPPHead, DepthwiseSeparableFCNHead, DMHead, DNLHead, EMAHead, EncHead, FCNHead, GCHead, LRASPPHead, NLHead, OCRHead, PointHead, PSAHead, PSPHead, UPerHead) from mmseg.models.decode_heads.decode_head import BaseDecodeHead def _conv_has_norm(module, sync_bn): for m in module.modules(): if isinstance(m, ConvModule): if not m.with_norm: return False if sync_bn: if not isinstance(m.bn, SyncBatchNorm): return False return True def to_cuda(module, data): module = module.cuda() if isinstance(data, list): for i in range(len(data)): data[i] = data[i].cuda() return module, data @patch.multiple(BaseDecodeHead, __abstractmethods__=set()) def test_decode_head(): with pytest.raises(AssertionError): # default input_transform doesn't accept multiple inputs BaseDecodeHead([32, 16], 16, num_classes=19) with pytest.raises(AssertionError): # default input_transform doesn't accept multiple inputs BaseDecodeHead(32, 16, num_classes=19, in_index=[-1, -2]) with pytest.raises(AssertionError): # supported mode is resize_concat only BaseDecodeHead(32, 16, num_classes=19, input_transform='concat') with pytest.raises(AssertionError): # in_channels should be list|tuple BaseDecodeHead(32, 16, num_classes=19, input_transform='resize_concat') with pytest.raises(AssertionError): # in_index should be list|tuple BaseDecodeHead([32], 16, in_index=-1, num_classes=19, input_transform='resize_concat') with pytest.raises(AssertionError): # len(in_index) should equal len(in_channels) BaseDecodeHead([32, 16], 16, num_classes=19, in_index=[-1], input_transform='resize_concat') # test default dropout head = BaseDecodeHead(32, 16, num_classes=19) assert hasattr(head, 'dropout') and head.dropout.p == 0.1 # test set dropout head = BaseDecodeHead(32, 16, num_classes=19, dropout_ratio=0.2) assert hasattr(head, 'dropout') and head.dropout.p == 0.2 # test no input_transform inputs = [torch.randn(1, 32, 45, 45)] head = BaseDecodeHead(32, 16, num_classes=19) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.in_channels == 32 assert head.input_transform is None transformed_inputs = head._transform_inputs(inputs) assert transformed_inputs.shape == (1, 32, 45, 45) # test input_transform = resize_concat inputs = [torch.randn(1, 32, 45, 45), torch.randn(1, 16, 21, 21)] head = BaseDecodeHead([32, 16], 16, num_classes=19, in_index=[0, 1], input_transform='resize_concat') if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.in_channels == 48 assert head.input_transform == 'resize_concat' transformed_inputs = head._transform_inputs(inputs) assert transformed_inputs.shape == (1, 48, 45, 45) def test_fcn_head(): with pytest.raises(AssertionError): # num_convs must be not less than 0 FCNHead(num_classes=19, num_convs=-1) # test no norm_cfg head = FCNHead(in_channels=32, channels=16, num_classes=19) for m in head.modules(): if isinstance(m, ConvModule): assert not m.with_norm # test with norm_cfg head = FCNHead( in_channels=32, channels=16, num_classes=19, norm_cfg=dict(type='BN')) for m in head.modules(): if isinstance(m, ConvModule): assert m.with_norm and isinstance(m.bn, SyncBatchNorm) # test concat_input=False inputs = [torch.randn(1, 32, 45, 45)] head = FCNHead( in_channels=32, channels=16, num_classes=19, concat_input=False) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert len(head.convs) == 2 assert not head.concat_input and not hasattr(head, 'conv_cat') outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # test concat_input=True inputs = [torch.randn(1, 32, 45, 45)] head = FCNHead( in_channels=32, channels=16, num_classes=19, concat_input=True) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert len(head.convs) == 2 assert head.concat_input assert head.conv_cat.in_channels == 48 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # test kernel_size=3 inputs = [torch.randn(1, 32, 45, 45)] head = FCNHead(in_channels=32, channels=16, num_classes=19) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) for i in range(len(head.convs)): assert head.convs[i].kernel_size == (3, 3) assert head.convs[i].padding == 1 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # test kernel_size=1 inputs = [torch.randn(1, 32, 45, 45)] head = FCNHead(in_channels=32, channels=16, num_classes=19, kernel_size=1) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) for i in range(len(head.convs)): assert head.convs[i].kernel_size == (1, 1) assert head.convs[i].padding == 0 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # test num_conv inputs = [torch.randn(1, 32, 45, 45)] head = FCNHead(in_channels=32, channels=16, num_classes=19, num_convs=1) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert len(head.convs) == 1 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # test num_conv = 0 inputs = [torch.randn(1, 32, 45, 45)] head = FCNHead( in_channels=32, channels=32, num_classes=19, num_convs=0, concat_input=False) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert isinstance(head.convs, torch.nn.Identity) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_psp_head(): with pytest.raises(AssertionError): # pool_scales must be list|tuple PSPHead(in_channels=32, channels=16, num_classes=19, pool_scales=1) # test no norm_cfg head = PSPHead(in_channels=32, channels=16, num_classes=19) assert not _conv_has_norm(head, sync_bn=False) # test with norm_cfg head = PSPHead( in_channels=32, channels=16, num_classes=19, norm_cfg=dict(type='BN')) assert _conv_has_norm(head, sync_bn=True) inputs = [torch.randn(1, 32, 45, 45)] head = PSPHead( in_channels=32, channels=16, num_classes=19, pool_scales=(1, 2, 3)) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.psp_modules[0][0].output_size == 1 assert head.psp_modules[1][0].output_size == 2 assert head.psp_modules[2][0].output_size == 3 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_apc_head(): with pytest.raises(AssertionError): # pool_scales must be list|tuple APCHead(in_channels=32, channels=16, num_classes=19, pool_scales=1) # test no norm_cfg head = APCHead(in_channels=32, channels=16, num_classes=19) assert not _conv_has_norm(head, sync_bn=False) # test with norm_cfg head = APCHead( in_channels=32, channels=16, num_classes=19, norm_cfg=dict(type='BN')) assert _conv_has_norm(head, sync_bn=True) # fusion=True inputs = [torch.randn(1, 32, 45, 45)] head = APCHead( in_channels=32, channels=16, num_classes=19, pool_scales=(1, 2, 3), fusion=True) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.fusion is True assert head.acm_modules[0].pool_scale == 1 assert head.acm_modules[1].pool_scale == 2 assert head.acm_modules[2].pool_scale == 3 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # fusion=False inputs = [torch.randn(1, 32, 45, 45)] head = APCHead( in_channels=32, channels=16, num_classes=19, pool_scales=(1, 2, 3), fusion=False) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.fusion is False assert head.acm_modules[0].pool_scale == 1 assert head.acm_modules[1].pool_scale == 2 assert head.acm_modules[2].pool_scale == 3 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_dm_head(): with pytest.raises(AssertionError): # filter_sizes must be list|tuple DMHead(in_channels=32, channels=16, num_classes=19, filter_sizes=1) # test no norm_cfg head = DMHead(in_channels=32, channels=16, num_classes=19) assert not _conv_has_norm(head, sync_bn=False) # test with norm_cfg head = DMHead( in_channels=32, channels=16, num_classes=19, norm_cfg=dict(type='BN')) assert _conv_has_norm(head, sync_bn=True) # fusion=True inputs = [torch.randn(1, 32, 45, 45)] head = DMHead( in_channels=32, channels=16, num_classes=19, filter_sizes=(1, 3, 5), fusion=True) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.fusion is True assert head.dcm_modules[0].filter_size == 1 assert head.dcm_modules[1].filter_size == 3 assert head.dcm_modules[2].filter_size == 5 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # fusion=False inputs = [torch.randn(1, 32, 45, 45)] head = DMHead( in_channels=32, channels=16, num_classes=19, filter_sizes=(1, 3, 5), fusion=False) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.fusion is False assert head.dcm_modules[0].filter_size == 1 assert head.dcm_modules[1].filter_size == 3 assert head.dcm_modules[2].filter_size == 5 outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_aspp_head(): with pytest.raises(AssertionError): # pool_scales must be list|tuple ASPPHead(in_channels=32, channels=16, num_classes=19, dilations=1) # test no norm_cfg head = ASPPHead(in_channels=32, channels=16, num_classes=19) assert not _conv_has_norm(head, sync_bn=False) # test with norm_cfg head = ASPPHead( in_channels=32, channels=16, num_classes=19, norm_cfg=dict(type='BN')) assert _conv_has_norm(head, sync_bn=True) inputs = [torch.randn(1, 32, 45, 45)] head = ASPPHead( in_channels=32, channels=16, num_classes=19, dilations=(1, 12, 24)) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.aspp_modules[0].conv.dilation == (1, 1) assert head.aspp_modules[1].conv.dilation == (12, 12) assert head.aspp_modules[2].conv.dilation == (24, 24) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_psa_head(): with pytest.raises(AssertionError): # psa_type must be in 'bi-direction', 'collect', 'distribute' PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39), psa_type='gather') # test no norm_cfg head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39)) assert not _conv_has_norm(head, sync_bn=False) # test with norm_cfg head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39), norm_cfg=dict(type='BN')) assert _conv_has_norm(head, sync_bn=True) # test 'bi-direction' psa_type inputs = [torch.randn(1, 32, 39, 39)] head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39)) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 39, 39) # test 'bi-direction' psa_type, shrink_factor=1 inputs = [torch.randn(1, 32, 39, 39)] head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39), shrink_factor=1) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 39, 39) # test 'bi-direction' psa_type with soft_max inputs = [torch.randn(1, 32, 39, 39)] head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39), psa_softmax=True) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 39, 39) # test 'collect' psa_type inputs = [torch.randn(1, 32, 39, 39)] head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39), psa_type='collect') if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 39, 39) # test 'collect' psa_type, shrink_factor=1 inputs = [torch.randn(1, 32, 39, 39)] head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39), shrink_factor=1, psa_type='collect') if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 39, 39) # test 'collect' psa_type, shrink_factor=1, compact=True inputs = [torch.randn(1, 32, 39, 39)] head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39), psa_type='collect', shrink_factor=1, compact=True) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 39, 39) # test 'distribute' psa_type inputs = [torch.randn(1, 32, 39, 39)] head = PSAHead( in_channels=32, channels=16, num_classes=19, mask_size=(39, 39), psa_type='distribute') if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 39, 39) def test_gc_head(): head = GCHead(in_channels=32, channels=16, num_classes=19) assert len(head.convs) == 2 assert hasattr(head, 'gc_block') inputs = [torch.randn(1, 32, 45, 45)] if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_nl_head(): head = NLHead(in_channels=32, channels=16, num_classes=19) assert len(head.convs) == 2 assert hasattr(head, 'nl_block') inputs = [torch.randn(1, 32, 45, 45)] if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_cc_head(): head = CCHead(in_channels=32, channels=16, num_classes=19) assert len(head.convs) == 2 assert hasattr(head, 'cca') if not torch.cuda.is_available(): pytest.skip('CCHead requires CUDA') inputs = [torch.randn(1, 32, 45, 45)] head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_uper_head(): with pytest.raises(AssertionError): # fpn_in_channels must be list|tuple UPerHead(in_channels=32, channels=16, num_classes=19) # test no norm_cfg head = UPerHead( in_channels=[32, 16], channels=16, num_classes=19, in_index=[-2, -1]) assert not _conv_has_norm(head, sync_bn=False) # test with norm_cfg head = UPerHead( in_channels=[32, 16], channels=16, num_classes=19, norm_cfg=dict(type='BN'), in_index=[-2, -1]) assert _conv_has_norm(head, sync_bn=True) inputs = [torch.randn(1, 32, 45, 45), torch.randn(1, 16, 21, 21)] head = UPerHead( in_channels=[32, 16], channels=16, num_classes=19, in_index=[-2, -1]) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_ann_head(): inputs = [torch.randn(1, 16, 45, 45), torch.randn(1, 32, 21, 21)] head = ANNHead( in_channels=[16, 32], channels=16, num_classes=19, in_index=[-2, -1], project_channels=8) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 21, 21) def test_da_head(): inputs = [torch.randn(1, 32, 45, 45)] head = DAHead(in_channels=32, channels=16, num_classes=19, pam_channels=8) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert isinstance(outputs, tuple) and len(outputs) == 3 for output in outputs: assert output.shape == (1, head.num_classes, 45, 45) test_output = head.forward_test(inputs, None, None) assert test_output.shape == (1, head.num_classes, 45, 45) def test_ocr_head(): inputs = [torch.randn(1, 32, 45, 45)] ocr_head = OCRHead( in_channels=32, channels=16, num_classes=19, ocr_channels=8) fcn_head = FCNHead(in_channels=32, channels=16, num_classes=19) if torch.cuda.is_available(): head, inputs = to_cuda(ocr_head, inputs) head, inputs = to_cuda(fcn_head, inputs) prev_output = fcn_head(inputs) output = ocr_head(inputs, prev_output) assert output.shape == (1, ocr_head.num_classes, 45, 45) def test_enc_head(): # with se_loss, w.o. lateral inputs = [torch.randn(1, 32, 21, 21)] head = EncHead( in_channels=[32], channels=16, num_classes=19, in_index=[-1]) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert isinstance(outputs, tuple) and len(outputs) == 2 assert outputs[0].shape == (1, head.num_classes, 21, 21) assert outputs[1].shape == (1, head.num_classes) # w.o se_loss, w.o. lateral inputs = [torch.randn(1, 32, 21, 21)] head = EncHead( in_channels=[32], channels=16, use_se_loss=False, num_classes=19, in_index=[-1]) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 21, 21) # with se_loss, with lateral inputs = [torch.randn(1, 16, 45, 45), torch.randn(1, 32, 21, 21)] head = EncHead( in_channels=[16, 32], channels=16, add_lateral=True, num_classes=19, in_index=[-2, -1]) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert isinstance(outputs, tuple) and len(outputs) == 2 assert outputs[0].shape == (1, head.num_classes, 21, 21) assert outputs[1].shape == (1, head.num_classes) test_output = head.forward_test(inputs, None, None) assert test_output.shape == (1, head.num_classes, 21, 21) def test_dw_aspp_head(): # test w.o. c1 inputs = [torch.randn(1, 32, 45, 45)] head = DepthwiseSeparableASPPHead( c1_in_channels=0, c1_channels=0, in_channels=32, channels=16, num_classes=19, dilations=(1, 12, 24)) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.c1_bottleneck is None assert head.aspp_modules[0].conv.dilation == (1, 1) assert head.aspp_modules[1].depthwise_conv.dilation == (12, 12) assert head.aspp_modules[2].depthwise_conv.dilation == (24, 24) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # test with c1 inputs = [torch.randn(1, 8, 45, 45), torch.randn(1, 32, 21, 21)] head = DepthwiseSeparableASPPHead( c1_in_channels=8, c1_channels=4, in_channels=32, channels=16, num_classes=19, dilations=(1, 12, 24)) if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) assert head.c1_bottleneck.in_channels == 8 assert head.c1_bottleneck.out_channels == 4 assert head.aspp_modules[0].conv.dilation == (1, 1) assert head.aspp_modules[1].depthwise_conv.dilation == (12, 12) assert head.aspp_modules[2].depthwise_conv.dilation == (24, 24) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_sep_fcn_head(): # test sep_fcn_head with concat_input=False head = DepthwiseSeparableFCNHead( in_channels=128, channels=128, concat_input=False, num_classes=19, in_index=-1, norm_cfg=dict(type='BN', requires_grad=True, momentum=0.01)) x = [torch.rand(2, 128, 32, 32)] output = head(x) assert output.shape == (2, head.num_classes, 32, 32) assert not head.concat_input assert isinstance(head.convs[0], DepthwiseSeparableConvModule) assert isinstance(head.convs[1], DepthwiseSeparableConvModule) assert head.conv_seg.kernel_size == (1, 1) head = DepthwiseSeparableFCNHead( in_channels=64, channels=64, concat_input=True, num_classes=19, in_index=-1, norm_cfg=dict(type='BN', requires_grad=True, momentum=0.01)) x = [torch.rand(3, 64, 32, 32)] output = head(x) assert output.shape == (3, head.num_classes, 32, 32) assert head.concat_input assert isinstance(head.convs[0], DepthwiseSeparableConvModule) assert isinstance(head.convs[1], DepthwiseSeparableConvModule) def test_dnl_head(): # DNL with 'embedded_gaussian' mode head = DNLHead(in_channels=32, channels=16, num_classes=19) assert len(head.convs) == 2 assert hasattr(head, 'dnl_block') assert head.dnl_block.temperature == 0.05 inputs = [torch.randn(1, 32, 45, 45)] if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # NonLocal2d with 'dot_product' mode head = DNLHead( in_channels=32, channels=16, num_classes=19, mode='dot_product') inputs = [torch.randn(1, 32, 45, 45)] if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # NonLocal2d with 'gaussian' mode head = DNLHead( in_channels=32, channels=16, num_classes=19, mode='gaussian') inputs = [torch.randn(1, 32, 45, 45)] if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) # NonLocal2d with 'concatenation' mode head = DNLHead( in_channels=32, channels=16, num_classes=19, mode='concatenation') inputs = [torch.randn(1, 32, 45, 45)] if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_emanet_head(): head = EMAHead( in_channels=32, ema_channels=24, channels=16, num_stages=3, num_bases=16, num_classes=19) for param in head.ema_mid_conv.parameters(): assert not param.requires_grad assert hasattr(head, 'ema_module') inputs = [torch.randn(1, 32, 45, 45)] if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45) def test_point_head(): inputs = [torch.randn(1, 32, 45, 45)] point_head = PointHead( in_channels=[32], in_index=[0], channels=16, num_classes=19) assert len(point_head.fcs) == 3 fcn_head = FCNHead(in_channels=32, channels=16, num_classes=19) if torch.cuda.is_available(): head, inputs = to_cuda(point_head, inputs) head, inputs = to_cuda(fcn_head, inputs) prev_output = fcn_head(inputs) test_cfg = ConfigDict( subdivision_steps=2, subdivision_num_points=8196, scale_factor=2) output = point_head.forward_test(inputs, prev_output, None, test_cfg) assert output.shape == (1, point_head.num_classes, 180, 180) def test_lraspp_head(): with pytest.raises(ValueError): # check invalid input_transform LRASPPHead( in_channels=(16, 16, 576), in_index=(0, 1, 2), channels=128, input_transform='resize_concat', dropout_ratio=0.1, num_classes=19, norm_cfg=dict(type='BN'), act_cfg=dict(type='ReLU'), align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)) with pytest.raises(AssertionError): # check invalid branch_channels LRASPPHead( in_channels=(16, 16, 576), in_index=(0, 1, 2), channels=128, branch_channels=64, input_transform='multiple_select', dropout_ratio=0.1, num_classes=19, norm_cfg=dict(type='BN'), act_cfg=dict(type='ReLU'), align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)) # test with default settings lraspp_head = LRASPPHead( in_channels=(16, 16, 576), in_index=(0, 1, 2), channels=128, input_transform='multiple_select', dropout_ratio=0.1, num_classes=19, norm_cfg=dict(type='BN'), act_cfg=dict(type='ReLU'), align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)) inputs = [ torch.randn(2, 16, 45, 45), torch.randn(2, 16, 28, 28), torch.randn(2, 576, 14, 14) ] with pytest.raises(RuntimeError): # check invalid inputs output = lraspp_head(inputs) inputs = [ torch.randn(2, 16, 111, 111), torch.randn(2, 16, 77, 77), torch.randn(2, 576, 55, 55) ] output = lraspp_head(inputs) assert output.shape == (2, 19, 111, 111)

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py

Python

mercadopago/config/__init__.py

nlgonzalez/sdk-python

972082b1a1c0015fce376a42f53e4696b163bc0b

[ "MIT" ]

100

2015-02-17T03:16:15.000Z

2022-03-28T17:22:14.000Z

mercadopago/config/__init__.py

nlgonzalez/sdk-python

972082b1a1c0015fce376a42f53e4696b163bc0b

[ "MIT" ]

29

2015-06-15T18:40:09.000Z

2022-02-24T15:36:03.000Z

mercadopago/config/__init__.py

nlgonzalez/sdk-python

972082b1a1c0015fce376a42f53e4696b163bc0b

[ "MIT" ]

58

2015-01-16T21:46:45.000Z

2022-02-25T21:26:22.000Z

""" Module: config/__init__.py """ from mercadopago.config.request_options import RequestOptions from mercadopago.config.config import Config

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py

Python

nlosExclusion/src/puGNSSPosCal.py

xiaoshitou4/GNSS-INS

6ea16568d85eb1ed6b5cc49fb192dcba0e0f7491

[ "Unlicense" ]

3

2019-07-27T05:31:15.000Z

2021-06-10T02:16:46.000Z

nlosExclusion/src/puGNSSPosCal.py

yxw027/GNSS-INS

e5c5b7901b270a9c4d3a0ffd5555843d969f4018

[ "Unlicense" ]

null

nlosExclusion/src/puGNSSPosCal.py

yxw027/GNSS-INS

e5c5b7901b270a9c4d3a0ffd5555843d969f4018

[ "Unlicense" ]

3

2019-12-25T07:47:22.000Z

2021-02-03T03:24:46.000Z

#!/usr/bin/env python # license removed for brevity """ GNSS positioning calculation Welson Wen, Ph.D. https://sites.google.com/view/weisongwen/about-me """ from numpy import * # numpy needed import matplotlib as mpl #plot needed mpl.use("TkAgg") # Use TKAgg to show figures:set this to show plot import matplotlib.pyplot as plt #plotting import pandas as pd # pandas needed renamed as pd import numpy as np #numpy needed renamed as np import geometry_msgs.msg as gm #ros geometry message from geometry_msgs.msg import Quaternion, Point, Pose, Twist,PoseArray # commonly used message type from sensor_msgs.msg import NavSatFix # standard message type for GNSSs from nlosExclusion.msg import GNSS_Raw_Array,GNSS_Raw # customerized ros message type from matplotlib.patches import Ellipse, Circle # draw circle needs library import csv # csv reading needed library import datetime #time format (datetime) import time #time format (time) import llh2ecef # llh to ecef import ecef2llh #ecef coordinate to llh coordinate from nlosExclusion.msg import Satellite_Info # customized ros message type Satellite_Info containing satellites exclusion numbers import rospy from novatel_msgs.msg import BESTPOS class GNSSPosCal(): def __init__(self): self.calMode = 'LSGPS' # 'LSGPS' 'LSGNSS' self.GNSSTim = 0 self.dop = 0 # dop self.toSv = 0 self.iterations_=0 self.appInfo = 0 self.prn = [] # prn self.snr = [] # snr self.pseudResid = {} # pseudorange residual self.visi = [] # visibility self.azimuth = [] self.elevation =[] self.ecef_=[] # calculation result self.llh_ =[] # self.GroTruth = [22.303953,114.181925,14.0] # for experiment1: small NLOS reception self.GroTruth = [22.303756,114.18215,14.0] # for experiment2: Big NLOS reception self.error_ = 0 self.GPSNum = [] # create a list to save GPS satellites numbers self.BeiNum = [] # create a list to save Beidou satellites numbers def LSGPSPosCalStep(self,GNSS_one_epoch_, init_x, init_y, init_z, init_b): # least square GNSS_one_epoch = GNSS_Raw_Array() GNSS_one_epoch = GNSS_one_epoch_ rec_ini_pos_x = float(init_x) # initial position x (m) rec_ini_pos_y = float(init_y) # initial position y (m) rec_ini_pos_z = float(init_z) # initial position z (m) rec_clo_bia_b = float(init_b) # initial distance bias caused by clock bias (m) devia_xyz = 1.0 # initial set receiver position estimation error (m) gues_pseud = [] # guessed pseudorange pseud_error = [] # pseudorange error G_matrix_ = array([2, 2, 2, 1], dtype='float') # creat G matrix to save transform parameters self.dop = self.DopCalculation(GNSS_one_epoch) for index_1 in range(len(GNSS_one_epoch.GNSS_Raws)): # index all the satellite information in one epoch if((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 88) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= (87 + 37))): if(self.iterations_<1): # save one time only self.GNSSTim = GNSS_one_epoch.GNSS_Raws[index_1].GNSS_time self.toSv = GNSS_one_epoch.GNSS_Raws[index_1].total_sv self.prn.append(GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index) self.snr.append(GNSS_one_epoch.GNSS_Raws[index_1].snr) self.visi.append(GNSS_one_epoch.GNSS_Raws[index_1].visable) self.azimuth.append(GNSS_one_epoch.GNSS_Raws[index_1].azimuth) self.elevation.append(GNSS_one_epoch.GNSS_Raws[index_1].elevation) sx_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_x) # satellite position x sy_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_y) # satellite position y sz_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_z) # satellite position z sx_1 = (sx_1 - rec_ini_pos_x) * (sx_1 - rec_ini_pos_x) # satellite to receiver distance in x idrection sy_1 = (sy_1 - rec_ini_pos_y) * (sy_1 - rec_ini_pos_y) # satellite to receiver distance in y idrection sz_1 = (sz_1 - rec_ini_pos_z) * (sz_1 - rec_ini_pos_z) # satellite to receiver distance in z idrection sat2rec_dis = sqrt(sx_1 + sy_1 + sz_1) # guessed pseudorange gues_pseud.append(sat2rec_dis) # save guessed pseudorange pseud_error_element = float(GNSS_one_epoch.GNSS_Raws[index_1].pseudorange) - float( sat2rec_dis) + float(rec_clo_bia_b) # pseudorange error pseud_error.append(pseud_error_element) # save pseudorange error G_row = [] # G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_x - rec_ini_pos_x) / float( sat2rec_dis) * -1) # x for G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_y - rec_ini_pos_y) / float( sat2rec_dis) * -1) # y for G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_z - rec_ini_pos_z) / float( sat2rec_dis) * -1) # z for G matrix row element_float = 1.0 # last element for each row G_row.append(element_float) # save last element for each row G_matrix_ = np.row_stack((G_matrix_, G_row)) # add each row to G_matrix del G_row[:] # relief G_row # get pseudorange error pseud_error_mat = np.array(pseud_error) # from list to array pseud_error_mat = pseud_error_mat.transpose() # transpose # get G matrix G_matrix_ = np.delete(G_matrix_, [0], axis=0) # delete the first row of G matrix delta_p = np.dot((G_matrix_.transpose()), G_matrix_) # G(T) * G delta_p_2 = np.linalg.inv(delta_p) # inverse matrix of G(T) * G delta_p = np.dot(delta_p_2, (G_matrix_.transpose())) # multiply (inverse matrix of G(T) * G) and G(T) delta_p = np.dot(delta_p, pseud_error_mat) # multiply with pseud_error_mat rec_ini_pos_x = rec_ini_pos_x + float(delta_p[0]) # update receiver position in x direction rec_ini_pos_y = rec_ini_pos_y + float(delta_p[1]) # update receiver position in y idrection rec_ini_pos_z = rec_ini_pos_z + float(delta_p[2]) # update receiver position in z idrection rec_clo_bia_b = rec_clo_bia_b + float(delta_p[3]) # update receiver clock bias in meters devia_x = float(delta_p[0]) # save delta x devia_y = float(delta_p[1]) # save delta y devia_z = float(delta_p[2]) # save delta z devia_b = float(delta_p[3]) # save delta bias devia_xyz = sqrt(devia_x * devia_x + devia_y * devia_y + devia_z * devia_z) # get total bias # print 'delta_p',delta_p # print 'position estimation x=',rec_ini_pos_x # print 'position estimation y=', rec_ini_pos_y # print 'position estimation Z=', rec_ini_pos_z # print 'position estimation b=', rec_clo_bia_b # print 'position estimation devia_xyz=', devia_xyz del gues_pseud[:] # relief gues_pseud[] list del pseud_error[:] # relief pseud_error[] list return float(rec_ini_pos_x), float(rec_ini_pos_y), float(rec_ini_pos_z), float(rec_clo_bia_b), float(devia_xyz) ''' GPS: 1:32 GLONASS: 32 + 1:24 Galileo: 57 + 1:30 Beidou: 87 + 1:37 QZSS: 124 + 1:4 ''' def LSGNSSPosCalStep(self,GNSS_one_epoch_, init_x, init_y, init_z, init_b_GPS, init_b_Beidou): # least square for hybrid GNSS positioning (GPS + Beidou) GNSS_one_epoch = GNSS_Raw_Array() GNSS_one_epoch = GNSS_one_epoch_ rec_ini_pos_x = float(init_x) # initial position x (m) rec_ini_pos_y = float(init_y) # initial position y (m) rec_ini_pos_z = float(init_z) # initial position z (m) rec_clo_bia_b_GPS = float(init_b_GPS) # initial distance bias caused by clock bias of GPS (m) rec_clo_bia_b_Beidou = float(init_b_Beidou) # initial distance bias caused by clock bias of Beidou (m) devia_xyz = 1.0 # initial set receiver position estimation error (m) gues_pseud = [] # guessed pseudorange pseud_error = [] # pseudorange error G_matrix_ = array([2, 2, 2, 1, 1], dtype='float') # creat G matrix to save transform parameters self.dop = self.DopCalculation(GNSS_one_epoch) # get guessed pseudorange and pseudorange error for index_1 in range(len(GNSS_one_epoch.GNSS_Raws)): # index all the satellite information in one epoch if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 88) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= (87 + 37)) or ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 1) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= 32))): if (self.iterations_ < 1): # save one time only self.GNSSTim = GNSS_one_epoch.GNSS_Raws[index_1].GNSS_time self.toSv = GNSS_one_epoch.GNSS_Raws[index_1].total_sv self.prn.append(GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index) self.snr.append(GNSS_one_epoch.GNSS_Raws[index_1].snr) self.visi.append(GNSS_one_epoch.GNSS_Raws[index_1].visable) self.azimuth.append(GNSS_one_epoch.GNSS_Raws[index_1].azimuth) self.elevation.append(GNSS_one_epoch.GNSS_Raws[index_1].elevation) sx_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_x) # satellite position x sy_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_y) # satellite position y sz_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_z) # satellite position z # print 'satellite index',GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index sx_1 = (sx_1 - rec_ini_pos_x) * ( sx_1 - rec_ini_pos_x) # satellite to receiver distance in x idrection sy_1 = (sy_1 - rec_ini_pos_y) * ( sy_1 - rec_ini_pos_y) # satellite to receiver distance in y idrection sz_1 = (sz_1 - rec_ini_pos_z) * ( sz_1 - rec_ini_pos_z) # satellite to receiver distance in z idrection sat2rec_dis = 0.0 # initialize variable sat2rec_dis = sqrt(sx_1 + sy_1 + sz_1) # guessed pseudorange gues_pseud.append(sat2rec_dis) # save guessed pseudorange G_row = [] # G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_x - rec_ini_pos_x) / float( sat2rec_dis) * -1) # x for G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_y - rec_ini_pos_y) / float( sat2rec_dis) * -1) # y for G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_z - rec_ini_pos_z) / float( sat2rec_dis) * -1) # z for G matrix row if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 88) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= (87 + 37))): element_float_GPS = 0.0 # GPS element for each row element_float_Beidou = 1.0 # Beidou element for each row G_row.append(element_float_GPS) # save last two element for each row G_row.append(element_float_Beidou) # save last two element for each row pseud_error_element = float(GNSS_one_epoch.GNSS_Raws[index_1].pseudorange) - float( sat2rec_dis) + float(rec_clo_bia_b_Beidou) # Beidou pseudorange error pseud_error.append(pseud_error_element) # save pseudorange error if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 1) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= 32)): element_float_GPS = 1.0 # GPS element for each row element_float_Beidou = 0.0 # Beidou element for each row G_row.append(element_float_GPS) # save last two element for each row G_row.append(element_float_Beidou) # save last two element for each row pseud_error_element = float(GNSS_one_epoch.GNSS_Raws[index_1].pseudorange) - float( sat2rec_dis) + float(rec_clo_bia_b_GPS) # GPS pseudorange error pseud_error.append(pseud_error_element) # save pseudorange error # print 'length of G_row',len(G_row),'GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index',GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index G_matrix_ = np.row_stack((G_matrix_, G_row)) # add each row to G_matrix del G_row[:] # relief G_row # get pseudorange error pseud_error_mat = np.array(pseud_error) # from list to array pseud_error_mat = pseud_error_mat.transpose() # transpose # get G matrix G_matrix_ = np.delete(G_matrix_, [0], axis=0) # delete the first row of G matrix # get cofactor matrix # cofactorMat_ = np.array(self.cofactorMatrixCal(GNSS_one_epoch_)) # cofactorMat_ = np.diag(cofactorMat_) # diag matrix # print 'cofactors', self.cofactorMatrixCal(GNSS_one_epoch_), cofactorMat_ delta_p = np.dot((G_matrix_.transpose()), G_matrix_) # G(T) * G delta_p_2 = np.linalg.inv(delta_p) # inverse matrix of G(T) * G delta_p = np.dot(delta_p_2, (G_matrix_.transpose())) # multiply (inverse matrix of G(T) * G) and G(T) delta_p = np.dot(delta_p, pseud_error_mat) # multiply with pseud_error_mat rec_ini_pos_x = rec_ini_pos_x + float(delta_p[0]) # update receiver position in x direction rec_ini_pos_y = rec_ini_pos_y + float(delta_p[1]) # update receiver position in y idrection rec_ini_pos_z = rec_ini_pos_z + float(delta_p[2]) # update receiver position in z idrection rec_clo_bia_b_GPS = rec_clo_bia_b_GPS + float(delta_p[3]) # update receiver clock bias of GPS in meters rec_clo_bia_b_Beidou = rec_clo_bia_b_Beidou + float( delta_p[4]) # update receiver clock bias of Beidou in meters devia_x = float(delta_p[0]) # save delta x devia_y = float(delta_p[1]) # save delta y devia_z = float(delta_p[2]) # save delta z devia_b_GPS = float(delta_p[3]) # save delta bias of GPS devia_b_Beidou = float(delta_p[4]) # save delta bias of Beidou devia_xyz = sqrt(devia_x * devia_x + devia_y * devia_y + devia_z * devia_z) # get total bias # print 'delta_p',delta_p # print 'position estimation x=',rec_ini_pos_x # print 'position estimation y=', rec_ini_pos_y # print 'position estimation Z=', rec_ini_pos_z # print 'position estimation b=', rec_clo_bia_b # print 'position estimation devia_xyz=', devia_xyz del gues_pseud[:] # relief gues_pseud[] list del pseud_error[:] # relief pseud_error[] list return float(rec_ini_pos_x), float(rec_ini_pos_y), float(rec_ini_pos_z), float(rec_clo_bia_b_GPS), float( rec_clo_bia_b_Beidou), float(devia_xyz) def WLSGNSSPosCalStep(self,GNSS_one_epoch_, init_x, init_y, init_z, init_b_GPS, init_b_Beidou): # least square for hybrid GNSS positioning (GPS + Beidou) GNSS_one_epoch = GNSS_Raw_Array() GNSS_one_epoch = GNSS_one_epoch_ rec_ini_pos_x = float(init_x) # initial position x (m) rec_ini_pos_y = float(init_y) # initial position y (m) rec_ini_pos_z = float(init_z) # initial position z (m) rec_clo_bia_b_GPS = float(init_b_GPS) # initial distance bias caused by clock bias of GPS (m) rec_clo_bia_b_Beidou = float(init_b_Beidou) # initial distance bias caused by clock bias of Beidou (m) devia_xyz = 1.0 # initial set receiver position estimation error (m) gues_pseud = [] # guessed pseudorange pseud_error = [] # pseudorange error G_matrix_ = array([2, 2, 2, 1, 1], dtype='float') # creat G matrix to save transform parameters self.dop = self.DopCalculation(GNSS_one_epoch) # get guessed pseudorange and pseudorange error for index_1 in range(len(GNSS_one_epoch.GNSS_Raws)): # index all the satellite information in one epoch if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 88) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= (87 + 37)) or ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 1) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= 32))): if (self.iterations_ < 1): # save one time only self.GNSSTim = GNSS_one_epoch.GNSS_Raws[index_1].GNSS_time self.toSv = GNSS_one_epoch.GNSS_Raws[index_1].total_sv self.prn.append(GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index) self.snr.append(GNSS_one_epoch.GNSS_Raws[index_1].snr) self.visi.append(GNSS_one_epoch.GNSS_Raws[index_1].visable) self.azimuth.append(GNSS_one_epoch.GNSS_Raws[index_1].azimuth) self.elevation.append(GNSS_one_epoch.GNSS_Raws[index_1].elevation) sx_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_x) # satellite position x sy_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_y) # satellite position y sz_1 = float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_z) # satellite position z # print 'satellite index',GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index sx_1 = (sx_1 - rec_ini_pos_x) * ( sx_1 - rec_ini_pos_x) # satellite to receiver distance in x idrection sy_1 = (sy_1 - rec_ini_pos_y) * ( sy_1 - rec_ini_pos_y) # satellite to receiver distance in y idrection sz_1 = (sz_1 - rec_ini_pos_z) * ( sz_1 - rec_ini_pos_z) # satellite to receiver distance in z idrection sat2rec_dis = 0.0 # initialize variable sat2rec_dis = sqrt(sx_1 + sy_1 + sz_1) # guessed pseudorange gues_pseud.append(sat2rec_dis) # save guessed pseudorange G_row = [] # G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_x - rec_ini_pos_x) / float( sat2rec_dis) * -1) # x for G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_y - rec_ini_pos_y) / float( sat2rec_dis) * -1) # y for G matrix row G_row.append(float(GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_z - rec_ini_pos_z) / float( sat2rec_dis) * -1) # z for G matrix row if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 88) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= (87 + 37))): element_float_GPS = 0.0 # GPS element for each row element_float_Beidou = 1.0 # Beidou element for each row G_row.append(element_float_GPS) # save last two element for each row G_row.append(element_float_Beidou) # save last two element for each row pseud_error_element = float(GNSS_one_epoch.GNSS_Raws[index_1].pseudorange) - float( sat2rec_dis) + float(rec_clo_bia_b_Beidou) # Beidou pseudorange error pseud_error.append(pseud_error_element) # save pseudorange error if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 1) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= 32)): element_float_GPS = 1.0 # GPS element for each row element_float_Beidou = 0.0 # Beidou element for each row G_row.append(element_float_GPS) # save last two element for each row G_row.append(element_float_Beidou) # save last two element for each row pseud_error_element = float(GNSS_one_epoch.GNSS_Raws[index_1].pseudorange) - float( sat2rec_dis) + float(rec_clo_bia_b_GPS) # GPS pseudorange error pseud_error.append(pseud_error_element) # save pseudorange error # print 'length of G_row',len(G_row),'GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index',GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index G_matrix_ = np.row_stack((G_matrix_, G_row)) # add each row to G_matrix del G_row[:] # relief G_row # get pseudorange error pseud_error_mat = np.array(pseud_error) # from list to array pseud_error_mat = pseud_error_mat.transpose() # transpose # get G matrix G_matrix_ = np.delete(G_matrix_, [0], axis=0) # delete the first row of G matrix # get cofactor matrix cofactorMat_ = np.array(self.cofactorMatrixCal(GNSS_one_epoch)) cofactorMat_ = np.diag(cofactorMat_) # diag matrix # print 'cofactors',self.cofactorMatrixCal(GNSS_one_epoch_),cofactorMat_,len(GNSS_one_epoch.GNSS_Raws) delta_p = np.dot((G_matrix_.transpose()), cofactorMat_) # G(T) * G delta_p = np.dot(delta_p, G_matrix_) # G(T) * G delta_p_2 = np.linalg.inv(delta_p) # inverse matrix of G(T) * G delta_p = np.dot(delta_p_2, (G_matrix_.transpose())) # multiply (inverse matrix of G(T) * G) and G(T) delta_p = np.dot(delta_p, cofactorMat_) # multiply (inverse matrix of G(T) * G) and G(T) delta_p = np.dot(delta_p, pseud_error_mat) # multiply with pseud_error_mat rec_ini_pos_x = rec_ini_pos_x + float(delta_p[0]) # update receiver position in x direction rec_ini_pos_y = rec_ini_pos_y + float(delta_p[1]) # update receiver position in y idrection rec_ini_pos_z = rec_ini_pos_z + float(delta_p[2]) # update receiver position in z idrection rec_clo_bia_b_GPS = rec_clo_bia_b_GPS + float(delta_p[3]) # update receiver clock bias of GPS in meters rec_clo_bia_b_Beidou = rec_clo_bia_b_Beidou + float( delta_p[4]) # update receiver clock bias of Beidou in meters devia_x = float(delta_p[0]) # save delta x devia_y = float(delta_p[1]) # save delta y devia_z = float(delta_p[2]) # save delta z devia_b_GPS = float(delta_p[3]) # save delta bias of GPS devia_b_Beidou = float(delta_p[4]) # save delta bias of Beidou devia_xyz = sqrt(devia_x * devia_x + devia_y * devia_y + devia_z * devia_z) # get total bias # print 'delta_p',delta_p # print 'position estimation x=',rec_ini_pos_x # print 'position estimation y=', rec_ini_pos_y # print 'position estimation Z=', rec_ini_pos_z # print 'position estimation b=', rec_clo_bia_b # print 'position estimation devia_xyz=', devia_xyz del gues_pseud[:] # relief gues_pseud[] list del pseud_error[:] # relief pseud_error[] list return float(rec_ini_pos_x), float(rec_ini_pos_y), float(rec_ini_pos_z), float(rec_clo_bia_b_GPS), float( rec_clo_bia_b_Beidou), float(devia_xyz) def iterPosCal(self,GNSS_one_epoch_,calMode): iterations = 0 itera_x = 0 itera_y = 0 itera_z = 0 self.calMode = calMode self.getSatNum(GNSS_one_epoch_) # get satellites numbers if(self.calMode=='LSGNSS') and (self.GPSNum>=4) and (self.BeiNum>1): itera_x, itera_y, itera_z, itera_b_GPS, itera_b_Beidou, itera_bias_ = self.LSGNSSPosCalStep( GNSS_one_epoch_, 0.1, 0.1, 0.1, 1.0, 1.0) # first iteration from (0.1, 0.1, 0.1, 1.0) self.iterations_ = self.iterations_+1 while (itera_bias_ > 1e-4) and iterations < 10: # threshold for iterations:value and times itera_x, itera_y, itera_z, itera_b_GPS, itera_b_Beidou, itera_bias_ = self.LSGNSSPosCalStep( GNSS_one_epoch_, itera_x, itera_y, itera_z, itera_b_GPS, itera_b_Beidou) # iteration self.iterations_ = self.iterations_ + 1 iterations = iterations + 1 # add one iteration elif (self.calMode == 'LSGPS') and (self.GPSNum>=4): itera_x, itera_y, itera_z, itera_b, itera_bias_ = self.LSGPSPosCalStep( GNSS_one_epoch_, 0.1, 0.1, 0.1, 1.0) # first iteration from (0.1, 0.1, 0.1, 1.0) self.iterations_ = self.iterations_ + 1 while (itera_bias_ > 1e-4) and iterations < 10: # threshold for iterations:value and times itera_x, itera_y, itera_z, itera_b, itera_bias_ = self.LSGPSPosCalStep( GNSS_one_epoch_,itera_x, itera_y,itera_z,itera_b) self.iterations_ = self.iterations_ + 1 iterations = iterations + 1 # add one iteration elif (self.calMode == 'WLSGNSS') and (self.GPSNum >= 4) and (self.BeiNum > 1): itera_x, itera_y, itera_z, itera_b_GPS, itera_b_Beidou, itera_bias_ = self.WLSGNSSPosCalStep( GNSS_one_epoch_, 0.1, 0.1, 0.1, 1.0, 1.0) # first iteration from (0.1, 0.1, 0.1, 1.0) self.iterations_ = self.iterations_ + 1 while (itera_bias_ > 1e-4) and iterations < 10: # threshold for iterations:value and times itera_x, itera_y, itera_z, itera_b_GPS, itera_b_Beidou, itera_bias_ = self.WLSGNSSPosCalStep( GNSS_one_epoch_, itera_x, itera_y, itera_z, itera_b_GPS, itera_b_Beidou) # iteration self.iterations_ = self.iterations_ + 1 iterations = iterations + 1 # add one iteration print 'itera_b_GPS',itera_b_GPS,'itera_b_Beidou-----------------------------------------',itera_b_Beidou self.ecef_.append(float(itera_x)) self.ecef_.append(float(itera_y)) self.ecef_.append(float(itera_z)) self.pseudoResCal(GNSS_one_epoch_) self.PosError() self.llh_ = ecef2llh.xyz2llh(self.ecef_) # ecef to llh coordinates iterations = 0.0 # initialize iterations variable # GNSSPosCal_ = puGNSSPosCal.GNSSPosCal() # GNSSPosCal_.iterGNSSPosCal(self.GNSSArr) def DopCalculation(self,GNSS_one_epoch_): # get Dop in one epoch GNSS_one_epoch = GNSS_Raw_Array() GNSS_one_epoch = GNSS_one_epoch_ H_matrix_ = array([2, 2, 2, 1], dtype='float') # creat H matrix to save transform parameters Hdop_ = 0.0 # create an variable to save Hdop elemin = 15.0 # minimun elevation angle for index_1 in range(len(GNSS_one_epoch.GNSS_Raws)): # index all the satellite information in one epoch if (GNSS_one_epoch.GNSS_Raws[index_1].elevation <= elemin): # print 'satellite elevation less than 15 degree=',GNSS_one_epoch.GNSS_Raws[index_1].elevation continue cosel = float(cos(GNSS_one_epoch.GNSS_Raws[index_1].elevation)) sinel = float(sin(GNSS_one_epoch.GNSS_Raws[index_1].elevation)) H_row = [] # H matrix row H_row.append(float(cosel * sin(GNSS_one_epoch.GNSS_Raws[index_1].azimuth))) H_row.append(float(cosel * cos(GNSS_one_epoch.GNSS_Raws[index_1].azimuth))) H_row.append(float(sinel)) H_row.append(1.0) H_matrix_ = np.row_stack((H_matrix_, H_row)) # add each row to H_matrix del H_row[:] # relief H_row # get H matrix H_matrix_ = np.delete(H_matrix_, [0], axis=0) # delete the first row of H matrix # print 'H_matrix_',H_matrix_ Q_matrix_ = np.dot((H_matrix_.transpose()), H_matrix_) # H(T) * G Q_matrix_ = np.linalg.inv(Q_matrix_) # inverse matrix of H(T) * G Hdop = float(sqrt(Q_matrix_[0, 0] + Q_matrix_[1, 1])) # print 'Q_matrix_', Q_matrix_, 'Hdop', Hdop return float(Hdop) # return result def getSatNum(self,GNSS_one_epoch): # get number of GPS and Beidou satellites in one epoch and save all the satellite number in list for index_1 in range(len(GNSS_one_epoch.GNSS_Raws)): # index all the satellite information in one epoch if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 1) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= 32)): # GPS satellites index range self.GPSNum.append(float(GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index)) if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 88) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= (87 + 37))): # Beidou satellites index range self.BeiNum.append(float(GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index)) def PosError(self): xyzTru_ = llh2ecef.llh2xyz(self.GroTruth) self.error_ = math.sqrt((self.ecef_[0]-xyzTru_[0]) * (self.ecef_[0]-xyzTru_[0]) + (self.ecef_[1]-xyzTru_[1]) * (self.ecef_[1]-xyzTru_[1]) + (self.ecef_[2]-xyzTru_[2]) * (self.ecef_[2]-xyzTru_[2])) if(self.error_ > 100): self.error_ = 100 def pseudoResCal(self,GNSS_one_epoch): for index_1 in range(len(GNSS_one_epoch.GNSS_Raws)): # index all the satellite information in one epoch pseudoRes_ = 0.0 res_x = GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_x - self.ecef_[0] res_y = GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_y - self.ecef_[1] res_z = GNSS_one_epoch.GNSS_Raws[index_1].sat_pos_z - self.ecef_[2] pseudoRes_ = int ((math.sqrt(res_x * res_x + res_y * res_y + res_z * res_z)) - GNSS_one_epoch.GNSS_Raws[index_1].pseudorange) satIdx_ = float(GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index) self.pseudResid[str(satIdx_)] = pseudoRes_ # print 'self.pseudResid=',self.pseudResid def cofactorMatrixCal(self,GNSS_one_epoch): snr_1 = 50.0 # T = 50 snr_A = 30.0 # A = 30 snr_a = 30.0 # a = 30 snr_0 = 10.0 # F = 10 cofactor_ = [] # cofactor of satellite for index_1 in range(len(GNSS_one_epoch.GNSS_Raws)): if ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 88) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= (87 + 37)) or ((GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index >= 1) and ( GNSS_one_epoch.GNSS_Raws[index_1].prn_satellites_index <= 32))): snr_R = GNSS_one_epoch.GNSS_Raws[index_1].snr elR = GNSS_one_epoch.GNSS_Raws[index_1].elevation q_R_1 = 1 / (( sin(elR * pi/180.0 )) ** 2) # q_R_1 = 1/q_R_1 q_R_2 = 10 ** (-(snr_R - snr_1) / snr_a) q_R_3 = (((snr_A / (10 ** (-(snr_0 - snr_1) / snr_a)) - 1) / (snr_0 - snr_1)) * (snr_R - snr_1) + 1) # q_R = float(1 / (( sin(elR * pi/180.0 )) ** 2) * (10 ** (-(snr_R - snr_1) / snr_a) * ( # (snr_A / (10 ** (-(snr_0 - snr_1) / snr_a)) - 1) / (snr_0 - snr_1) * (snr_R - snr_1) + 1))) q_R = q_R_1* (q_R_2 * q_R_3) cofactor_.append(float(1.0/q_R)) return cofactor_

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Python

mapping/data_loader/__init__.py

syanga/model-augmented-mutual-information

a7c0ccb3b32320e9c45c266d668a879e240d39e3

[ "MIT" ]

2

2021-06-10T05:45:16.000Z

2021-11-06T11:44:42.000Z

mapping/data_loader/__init__.py

syanga/model-augmented-mutual-information

a7c0ccb3b32320e9c45c266d668a879e240d39e3

[ "MIT" ]

null

mapping/data_loader/__init__.py

syanga/model-augmented-mutual-information

a7c0ccb3b32320e9c45c266d668a879e240d39e3

[ "MIT" ]

null

from .np_supervised import * from .h5_supervised import * from .h5_timeseries import *

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Python

flat_api/api/collection_api.py

FlatIO/api-client-python

898d1da77989b3e9075f0311b6a4d342a72e95ef

[ "Apache-2.0" ]

8

2017-04-09T15:54:12.000Z

2021-07-14T13:38:43.000Z

flat_api/api/collection_api.py

FlatIO/api-client-python

898d1da77989b3e9075f0311b6a4d342a72e95ef

[ "Apache-2.0" ]

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2018-07-20T13:22:40.000Z

2022-03-23T20:03:21.000Z

flat_api/api/collection_api.py

FlatIO/api-client-python

898d1da77989b3e9075f0311b6a4d342a72e95ef

[ "Apache-2.0" ]

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2018-07-23T07:16:13.000Z

# coding: utf-8 """ Flat API The Flat API allows you to easily extend the abilities of the [Flat Platform](https://flat.io), with a wide range of use cases including the following: * Creating and importing new music scores using MusicXML, MIDI, Guitar Pro (GP3, GP4, GP5, GPX, GP), PowerTab, TuxGuitar and MuseScore files * Browsing, updating, copying, exporting the user's scores (for example in MP3, WAV or MIDI) * Managing educational resources with Flat for Education: creating & updating the organization accounts, the classes, rosters and assignments. The Flat API is built on HTTP. Our API is RESTful It has predictable resource URLs. It returns HTTP response codes to indicate errors. It also accepts and returns JSON in the HTTP body. The [schema](/swagger.yaml) of this API follows the [OpenAPI Initiative (OAI) specification](https://www.openapis.org/), you can use and work with [compatible Swagger tools](http://swagger.io/open-source-integrations/). This API features Cross-Origin Resource Sharing (CORS) implemented in compliance with [W3C spec](https://www.w3.org/TR/cors/). You can use your favorite HTTP/REST library for your programming language to use Flat's API. This specification and reference is [available on Github](https://github.com/FlatIO/api-reference). Getting Started and learn more: * [API Overview and interoduction](https://flat.io/developers/docs/api/) * [Authentication (Personal Access Tokens or OAuth2)](https://flat.io/developers/docs/api/authentication.html) * [SDKs](https://flat.io/developers/docs/api/sdks.html) * [Rate Limits](https://flat.io/developers/docs/api/rate-limits.html) * [Changelog](https://flat.io/developers/docs/api/changelog.html) # noqa: E501 OpenAPI spec version: 2.7.0 Contact: developers@flat.io Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from flat_api.api_client import ApiClient class CollectionApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def add_score_to_collection(self, collection, score, **kwargs): # noqa: E501 """Add a score to the collection # noqa: E501 This operation will add a score to a collection. The default behavior will make the score available across multiple collections. You must have the capability `canAddScores` on the provided `collection` to perform the action. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.add_score_to_collection(collection, score, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param str score: Unique identifier of the score document. This can be a Flat Score unique identifier (i.e. `ScoreDetails.id`) or, if the score is also a Google Drive file, the Drive file unique identifier prefixed with `drive-` (e.g. `drive-0B000000000`). (required) :param str sharing_key: This sharing key must be specified to access to a score or collection with a `privacy` mode set to `privateLink` and the current user is not a collaborator of the document. :return: ScoreDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.add_score_to_collection_with_http_info(collection, score, **kwargs) # noqa: E501 else: (data) = self.add_score_to_collection_with_http_info(collection, score, **kwargs) # noqa: E501 return data def add_score_to_collection_with_http_info(self, collection, score, **kwargs): # noqa: E501 """Add a score to the collection # noqa: E501 This operation will add a score to a collection. The default behavior will make the score available across multiple collections. You must have the capability `canAddScores` on the provided `collection` to perform the action. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.add_score_to_collection_with_http_info(collection, score, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param str score: Unique identifier of the score document. This can be a Flat Score unique identifier (i.e. `ScoreDetails.id`) or, if the score is also a Google Drive file, the Drive file unique identifier prefixed with `drive-` (e.g. `drive-0B000000000`). (required) :param str sharing_key: This sharing key must be specified to access to a score or collection with a `privacy` mode set to `privateLink` and the current user is not a collaborator of the document. :return: ScoreDetails If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['collection', 'score', 'sharing_key'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method add_score_to_collection" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'collection' is set if ('collection' not in local_var_params or local_var_params['collection'] is None): raise ValueError("Missing the required parameter `collection` when calling `add_score_to_collection`") # noqa: E501 # verify the required parameter 'score' is set if ('score' not in local_var_params or local_var_params['score'] is None): raise ValueError("Missing the required parameter `score` when calling `add_score_to_collection`") # noqa: E501 collection_formats = {} path_params = {} if 'collection' in local_var_params: path_params['collection'] = local_var_params['collection'] # noqa: E501 if 'score' in local_var_params: path_params['score'] = local_var_params['score'] # noqa: E501 query_params = [] if 'sharing_key' in local_var_params: query_params.append(('sharingKey', local_var_params['sharing_key'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections/{collection}/scores/{score}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ScoreDetails', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def create_collection(self, collection_creation, **kwargs): # noqa: E501 """Create a new collection # noqa: E501 This method will create a new collection and add it to your `root` collection. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_collection(collection_creation, async_req=True) >>> result = thread.get() :param async_req bool :param CollectionCreation collection_creation: (required) :return: Collection If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_collection_with_http_info(collection_creation, **kwargs) # noqa: E501 else: (data) = self.create_collection_with_http_info(collection_creation, **kwargs) # noqa: E501 return data def create_collection_with_http_info(self, collection_creation, **kwargs): # noqa: E501 """Create a new collection # noqa: E501 This method will create a new collection and add it to your `root` collection. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_collection_with_http_info(collection_creation, async_req=True) >>> result = thread.get() :param async_req bool :param CollectionCreation collection_creation: (required) :return: Collection If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['collection_creation'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_collection" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'collection_creation' is set if ('collection_creation' not in local_var_params or local_var_params['collection_creation'] is None): raise ValueError("Missing the required parameter `collection_creation` when calling `create_collection`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'collection_creation' in local_var_params: body_params = local_var_params['collection_creation'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Collection', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def delete_collection(self, collection, **kwargs): # noqa: E501 """Delete the collection # noqa: E501 This method will schedule the deletion of the collection. Until deleted, the collection will be available in the `trash`. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_collection(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_collection_with_http_info(collection, **kwargs) # noqa: E501 else: (data) = self.delete_collection_with_http_info(collection, **kwargs) # noqa: E501 return data def delete_collection_with_http_info(self, collection, **kwargs): # noqa: E501 """Delete the collection # noqa: E501 This method will schedule the deletion of the collection. Until deleted, the collection will be available in the `trash`. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_collection_with_http_info(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :return: None If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['collection'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_collection" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'collection' is set if ('collection' not in local_var_params or local_var_params['collection'] is None): raise ValueError("Missing the required parameter `collection` when calling `delete_collection`") # noqa: E501 collection_formats = {} path_params = {} if 'collection' in local_var_params: path_params['collection'] = local_var_params['collection'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections/{collection}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def delete_score_from_collection(self, collection, score, **kwargs): # noqa: E501 """Delete a score from the collection # noqa: E501 This method will delete a score from the collection. Unlike [`DELETE /scores/{score}`](#operation/deleteScore), this score will not remove the score from your account, but only from the collection. This can be used to *move* a score from one collection to another, or simply remove a score from one collection when this one is contained in multiple collections. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_score_from_collection(collection, score, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param str score: Unique identifier of the score document. This can be a Flat Score unique identifier (i.e. `ScoreDetails.id`) or, if the score is also a Google Drive file, the Drive file unique identifier prefixed with `drive-` (e.g. `drive-0B000000000`). (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_score_from_collection_with_http_info(collection, score, **kwargs) # noqa: E501 else: (data) = self.delete_score_from_collection_with_http_info(collection, score, **kwargs) # noqa: E501 return data def delete_score_from_collection_with_http_info(self, collection, score, **kwargs): # noqa: E501 """Delete a score from the collection # noqa: E501 This method will delete a score from the collection. Unlike [`DELETE /scores/{score}`](#operation/deleteScore), this score will not remove the score from your account, but only from the collection. This can be used to *move* a score from one collection to another, or simply remove a score from one collection when this one is contained in multiple collections. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_score_from_collection_with_http_info(collection, score, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param str score: Unique identifier of the score document. This can be a Flat Score unique identifier (i.e. `ScoreDetails.id`) or, if the score is also a Google Drive file, the Drive file unique identifier prefixed with `drive-` (e.g. `drive-0B000000000`). (required) :return: None If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['collection', 'score'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_score_from_collection" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'collection' is set if ('collection' not in local_var_params or local_var_params['collection'] is None): raise ValueError("Missing the required parameter `collection` when calling `delete_score_from_collection`") # noqa: E501 # verify the required parameter 'score' is set if ('score' not in local_var_params or local_var_params['score'] is None): raise ValueError("Missing the required parameter `score` when calling `delete_score_from_collection`") # noqa: E501 collection_formats = {} path_params = {} if 'collection' in local_var_params: path_params['collection'] = local_var_params['collection'] # noqa: E501 if 'score' in local_var_params: path_params['score'] = local_var_params['score'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections/{collection}/scores/{score}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def edit_collection(self, collection, **kwargs): # noqa: E501 """Update a collection's metadata # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_collection(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param CollectionModification collection_modification: :return: Collection If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.edit_collection_with_http_info(collection, **kwargs) # noqa: E501 else: (data) = self.edit_collection_with_http_info(collection, **kwargs) # noqa: E501 return data def edit_collection_with_http_info(self, collection, **kwargs): # noqa: E501 """Update a collection's metadata # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.edit_collection_with_http_info(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param CollectionModification collection_modification: :return: Collection If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['collection', 'collection_modification'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method edit_collection" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'collection' is set if ('collection' not in local_var_params or local_var_params['collection'] is None): raise ValueError("Missing the required parameter `collection` when calling `edit_collection`") # noqa: E501 collection_formats = {} path_params = {} if 'collection' in local_var_params: path_params['collection'] = local_var_params['collection'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'collection_modification' in local_var_params: body_params = local_var_params['collection_modification'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections/{collection}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Collection', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def get_collection(self, collection, **kwargs): # noqa: E501 """Get collection details # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_collection(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param str sharing_key: This sharing key must be specified to access to a score or collection with a `privacy` mode set to `privateLink` and the current user is not a collaborator of the document. :return: Collection If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_collection_with_http_info(collection, **kwargs) # noqa: E501 else: (data) = self.get_collection_with_http_info(collection, **kwargs) # noqa: E501 return data def get_collection_with_http_info(self, collection, **kwargs): # noqa: E501 """Get collection details # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_collection_with_http_info(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param str sharing_key: This sharing key must be specified to access to a score or collection with a `privacy` mode set to `privateLink` and the current user is not a collaborator of the document. :return: Collection If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['collection', 'sharing_key'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_collection" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'collection' is set if ('collection' not in local_var_params or local_var_params['collection'] is None): raise ValueError("Missing the required parameter `collection` when calling `get_collection`") # noqa: E501 collection_formats = {} path_params = {} if 'collection' in local_var_params: path_params['collection'] = local_var_params['collection'] # noqa: E501 query_params = [] if 'sharing_key' in local_var_params: query_params.append(('sharingKey', local_var_params['sharing_key'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections/{collection}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Collection', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def list_collection_scores(self, collection, **kwargs): # noqa: E501 """List the scores contained in a collection # noqa: E501 Use this method to list the scores contained in a collection. If no sort option is provided, the scores are sorted by `modificationDate` `desc`. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_collection_scores(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param str sharing_key: This sharing key must be specified to access to a score or collection with a `privacy` mode set to `privateLink` and the current user is not a collaborator of the document. :param str sort: Sort :param str direction: Sort direction :param int limit: This is the maximum number of objects that may be returned :param str next: An opaque string cursor to fetch the next page of data. The paginated API URLs are returned in the `Link` header when requesting the API. These URLs will contain a `next` and `previous` cursor based on the available data. :param str previous: An opaque string cursor to fetch the previous page of data. The paginated API URLs are returned in the `Link` header when requesting the API. These URLs will contain a `next` and `previous` cursor based on the available data. :return: list[ScoreDetails] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.list_collection_scores_with_http_info(collection, **kwargs) # noqa: E501 else: (data) = self.list_collection_scores_with_http_info(collection, **kwargs) # noqa: E501 return data def list_collection_scores_with_http_info(self, collection, **kwargs): # noqa: E501 """List the scores contained in a collection # noqa: E501 Use this method to list the scores contained in a collection. If no sort option is provided, the scores are sorted by `modificationDate` `desc`. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_collection_scores_with_http_info(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :param str sharing_key: This sharing key must be specified to access to a score or collection with a `privacy` mode set to `privateLink` and the current user is not a collaborator of the document. :param str sort: Sort :param str direction: Sort direction :param int limit: This is the maximum number of objects that may be returned :param str next: An opaque string cursor to fetch the next page of data. The paginated API URLs are returned in the `Link` header when requesting the API. These URLs will contain a `next` and `previous` cursor based on the available data. :param str previous: An opaque string cursor to fetch the previous page of data. The paginated API URLs are returned in the `Link` header when requesting the API. These URLs will contain a `next` and `previous` cursor based on the available data. :return: list[ScoreDetails] If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['collection', 'sharing_key', 'sort', 'direction', 'limit', 'next', 'previous'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method list_collection_scores" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'collection' is set if ('collection' not in local_var_params or local_var_params['collection'] is None): raise ValueError("Missing the required parameter `collection` when calling `list_collection_scores`") # noqa: E501 if 'limit' in local_var_params and local_var_params['limit'] > 100: # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `list_collection_scores`, must be a value less than or equal to `100`") # noqa: E501 if 'limit' in local_var_params and local_var_params['limit'] < 1: # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `list_collection_scores`, must be a value greater than or equal to `1`") # noqa: E501 collection_formats = {} path_params = {} if 'collection' in local_var_params: path_params['collection'] = local_var_params['collection'] # noqa: E501 query_params = [] if 'sharing_key' in local_var_params: query_params.append(('sharingKey', local_var_params['sharing_key'])) # noqa: E501 if 'sort' in local_var_params: query_params.append(('sort', local_var_params['sort'])) # noqa: E501 if 'direction' in local_var_params: query_params.append(('direction', local_var_params['direction'])) # noqa: E501 if 'limit' in local_var_params: query_params.append(('limit', local_var_params['limit'])) # noqa: E501 if 'next' in local_var_params: query_params.append(('next', local_var_params['next'])) # noqa: E501 if 'previous' in local_var_params: query_params.append(('previous', local_var_params['previous'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections/{collection}/scores', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[ScoreDetails]', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def list_collections(self, **kwargs): # noqa: E501 """List the collections # noqa: E501 Use this method to list the user's collections contained in `parent` (by default in the `root` collection). If no sort option is provided, the collections are sorted by `creationDate` `desc`. Note that this method will not include the `parent` collection in the listing. For example, if you need the details of the `root` collection, you can use `GET /v2/collections/root`. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_collections(async_req=True) >>> result = thread.get() :param async_req bool :param str parent: List the collection contained in this `parent` collection. This option doesn't provide a complete multi-level collection support. When sharing a collection with someone, this one will have as `parent` `sharedWithMe`. :param str sort: Sort :param str direction: Sort direction :param int limit: This is the maximum number of objects that may be returned :param str next: An opaque string cursor to fetch the next page of data. The paginated API URLs are returned in the `Link` header when requesting the API. These URLs will contain a `next` and `previous` cursor based on the available data. :param str previous: An opaque string cursor to fetch the previous page of data. The paginated API URLs are returned in the `Link` header when requesting the API. These URLs will contain a `next` and `previous` cursor based on the available data. :return: list[Collection] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.list_collections_with_http_info(**kwargs) # noqa: E501 else: (data) = self.list_collections_with_http_info(**kwargs) # noqa: E501 return data def list_collections_with_http_info(self, **kwargs): # noqa: E501 """List the collections # noqa: E501 Use this method to list the user's collections contained in `parent` (by default in the `root` collection). If no sort option is provided, the collections are sorted by `creationDate` `desc`. Note that this method will not include the `parent` collection in the listing. For example, if you need the details of the `root` collection, you can use `GET /v2/collections/root`. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_collections_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param str parent: List the collection contained in this `parent` collection. This option doesn't provide a complete multi-level collection support. When sharing a collection with someone, this one will have as `parent` `sharedWithMe`. :param str sort: Sort :param str direction: Sort direction :param int limit: This is the maximum number of objects that may be returned :param str next: An opaque string cursor to fetch the next page of data. The paginated API URLs are returned in the `Link` header when requesting the API. These URLs will contain a `next` and `previous` cursor based on the available data. :param str previous: An opaque string cursor to fetch the previous page of data. The paginated API URLs are returned in the `Link` header when requesting the API. These URLs will contain a `next` and `previous` cursor based on the available data. :return: list[Collection] If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['parent', 'sort', 'direction', 'limit', 'next', 'previous'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method list_collections" % key ) local_var_params[key] = val del local_var_params['kwargs'] if 'limit' in local_var_params and local_var_params['limit'] > 100: # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `list_collections`, must be a value less than or equal to `100`") # noqa: E501 if 'limit' in local_var_params and local_var_params['limit'] < 1: # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `list_collections`, must be a value greater than or equal to `1`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'parent' in local_var_params: query_params.append(('parent', local_var_params['parent'])) # noqa: E501 if 'sort' in local_var_params: query_params.append(('sort', local_var_params['sort'])) # noqa: E501 if 'direction' in local_var_params: query_params.append(('direction', local_var_params['direction'])) # noqa: E501 if 'limit' in local_var_params: query_params.append(('limit', local_var_params['limit'])) # noqa: E501 if 'next' in local_var_params: query_params.append(('next', local_var_params['next'])) # noqa: E501 if 'previous' in local_var_params: query_params.append(('previous', local_var_params['previous'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[Collection]', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def untrash_collection(self, collection, **kwargs): # noqa: E501 """Untrash a collection # noqa: E501 This method will restore the collection by removing it from the `trash` and add it back to the `root` collection. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.untrash_collection(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.untrash_collection_with_http_info(collection, **kwargs) # noqa: E501 else: (data) = self.untrash_collection_with_http_info(collection, **kwargs) # noqa: E501 return data def untrash_collection_with_http_info(self, collection, **kwargs): # noqa: E501 """Untrash a collection # noqa: E501 This method will restore the collection by removing it from the `trash` and add it back to the `root` collection. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.untrash_collection_with_http_info(collection, async_req=True) >>> result = thread.get() :param async_req bool :param str collection: Unique identifier of the collection. The following aliases are supported: - `root`: The root collection of the account - `sharedWithMe`: Automatically contains new resources that have been shared individually - `trash`: Automatically contains resources that have been deleted (required) :return: None If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = ['collection'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method untrash_collection" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'collection' is set if ('collection' not in local_var_params or local_var_params['collection'] is None): raise ValueError("Missing the required parameter `collection` when calling `untrash_collection`") # noqa: E501 collection_formats = {} path_params = {} if 'collection' in local_var_params: path_params['collection'] = local_var_params['collection'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['OAuth2'] # noqa: E501 return self.api_client.call_api( '/collections/{collection}/untrash', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats)

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1

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1

0

null

0

8

b26464838281bee912d2363619722a03f8f03b88

64

py

Python

go/dlgo/ttt/__init__.py

huynq55/alpha-zero-general

7c7b8a9a09b79178157ec6b6d379a071c9f0994a

[ "MIT" ]

1

2021-04-20T23:01:22.000Z

go/dlgo/ttt/__init__.py

huynq55/alpha-zero-general

7c7b8a9a09b79178157ec6b6d379a071c9f0994a

[ "MIT" ]

null

go/dlgo/ttt/__init__.py

huynq55/alpha-zero-general

7c7b8a9a09b79178157ec6b6d379a071c9f0994a

[ "MIT" ]

null

from dlgo.ttt.tttboard import * from dlgo.ttt.ttttypes import *

21.333333

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7

b2a008af79069cf3277d72c67f254213a558af97

12,755

py

Python

model/model_RelationalReasoning.py

haoyfan/SelfTime

28cafe1171bcd2f300242fe0703840478ae53bf0

[ "MIT" ]

41

2020-10-08T12:27:02.000Z

2022-02-07T03:28:56.000Z

model/model_RelationalReasoning.py

haoyfan/SelfTime

28cafe1171bcd2f300242fe0703840478ae53bf0

[ "MIT" ]

null

model/model_RelationalReasoning.py

haoyfan/SelfTime

28cafe1171bcd2f300242fe0703840478ae53bf0

[ "MIT" ]

13

2021-01-15T03:17:55.000Z

2022-03-23T19:04:29.000Z

# -*- coding: utf-8 -*- import torch from optim.pytorchtools import EarlyStopping import torch.nn as nn class RelationalReasoning(torch.nn.Module): def __init__(self, backbone, feature_size=64): super(RelationalReasoning, self).__init__() self.backbone = backbone self.relation_head = torch.nn.Sequential( torch.nn.Linear(feature_size*2, 256), torch.nn.BatchNorm1d(256), torch.nn.LeakyReLU(), torch.nn.Linear(256, 1)) def aggregate(self, features, K): relation_pairs_list = list() targets_list = list() size = int(features.shape[0] / K) shifts_counter=1 for index_1 in range(0, size*K, size): for index_2 in range(index_1+size, size*K, size): # Using the 'cat' aggregation function by default pos1 = features[index_1:index_1 + size] pos2 = features[index_2:index_2+size] pos_pair = torch.cat([pos1, pos2], 1) # (batch_size, fz*2) # Shuffle without collisions by rolling the mini-batch (negatives) neg1 = torch.roll(features[index_2:index_2 + size], shifts=shifts_counter, dims=0) neg_pair1 = torch.cat([pos1, neg1], 1) # (batch_size, fz*2) relation_pairs_list.append(pos_pair) relation_pairs_list.append(neg_pair1) targets_list.append(torch.ones(size, dtype=torch.float32).cuda()) targets_list.append(torch.zeros(size, dtype=torch.float32).cuda()) shifts_counter+=1 if(shifts_counter>=size): shifts_counter=1 # avoid identity pairs relation_pairs = torch.cat(relation_pairs_list, 0).cuda() # K(K-1) * (batch_size, fz*2) targets = torch.cat(targets_list, 0).cuda() return relation_pairs, targets def train(self, tot_epochs, train_loader, opt): patience = opt.patience early_stopping = EarlyStopping(patience, verbose=True, checkpoint_pth='{}/backbone_best.tar'.format(opt.ckpt_dir)) optimizer = torch.optim.Adam([ {'params': self.backbone.parameters()}, {'params': self.relation_head.parameters()}], lr=opt.learning_rate) BCE = torch.nn.BCEWithLogitsLoss() self.backbone.train() self.relation_head.train() epoch_max = 0 acc_max=0 for epoch in range(tot_epochs): acc_epoch=0 loss_epoch=0 # the real target is discarded (unsupervised) for i, (data_augmented, _) in enumerate(train_loader): K = len(data_augmented) # tot augmentations x = torch.cat(data_augmented, 0).cuda() optimizer.zero_grad() # forward pass (backbone) features = self.backbone(x) # aggregation function relation_pairs, targets = self.aggregate(features, K) # forward pass (relation head) score = self.relation_head(relation_pairs).squeeze() # cross-entropy loss and backward loss = BCE(score, targets) loss.backward() optimizer.step() # estimate the accuracy predicted = torch.round(torch.sigmoid(score)) correct = predicted.eq(targets.view_as(predicted)).sum() accuracy = (100.0 * correct / float(len(targets))) acc_epoch += accuracy.item() loss_epoch += loss.item() acc_epoch /= len(train_loader) loss_epoch /= len(train_loader) if acc_epoch>acc_max: acc_max = acc_epoch epoch_max = epoch early_stopping(acc_epoch, self.backbone) if early_stopping.early_stop: print("Early stopping") break if (epoch+1)%opt.save_freq==0: print("[INFO] save backbone at epoch {}!".format(epoch)) torch.save(self.backbone.state_dict(), '{}/backbone_{}.tar'.format(opt.ckpt_dir, epoch)) print('Epoch [{}][{}][{}] loss= {:.5f}; Epoch ACC.= {:.2f}%, Max ACC.= {:.1f}%, Max Epoch={}' \ .format(epoch + 1, opt.model_name, opt.dataset_name, loss_epoch, acc_epoch, acc_max, epoch_max)) return acc_max, epoch_max class RelationalReasoning_Intra(torch.nn.Module): def __init__(self, backbone, feature_size=64, nb_class=3): super(RelationalReasoning_Intra, self).__init__() self.backbone = backbone self.cls_head = torch.nn.Sequential( torch.nn.Linear(feature_size*2, 256), torch.nn.BatchNorm1d(256), torch.nn.LeakyReLU(), torch.nn.Linear(256, nb_class), torch.nn.Softmax(), ) def run_test(self, predict, labels): correct = 0 pred = predict.data.max(1)[1] correct = pred.eq(labels.data).cpu().sum() return correct, len(labels.data) def train(self, tot_epochs, train_loader, opt): patience = opt.patience early_stopping = EarlyStopping(patience, verbose=True, checkpoint_pth='{}/backbone_best.tar'.format(opt.ckpt_dir)) optimizer = torch.optim.Adam([ {'params': self.backbone.parameters()}, {'params': self.cls_head.parameters()}, ], lr=opt.learning_rate) c_criterion = nn.CrossEntropyLoss() self.backbone.train() self.cls_head.train() epoch_max = 0 acc_max=0 for epoch in range(tot_epochs): acc_epoch=0 acc_epoch_cls=0 loss_epoch=0 # the real target is discarded (unsupervised) for i, (data_augmented0, data_augmented1, data_label, _) in enumerate(train_loader): K = len(data_augmented0) # tot augmentations x_cut0 = torch.cat(data_augmented0, 0).cuda() x_cut1 = torch.cat(data_augmented1, 0).cuda() c_label = torch.cat(data_label, 0).cuda() optimizer.zero_grad() # forward pass (backbone) features_cut0 = self.backbone(x_cut0) features_cut1 = self.backbone(x_cut1) features_cls = torch.cat([features_cut0, features_cut1], 1) # score_intra = self.relation_head(relation_pairs_intra).squeeze() c_output = self.cls_head(features_cls) correct_cls, length_cls = self.run_test(c_output, c_label) loss_c = c_criterion(c_output, c_label) loss=loss_c loss.backward() optimizer.step() # estimate the accuracy loss_epoch += loss.item() accuracy_cls = 100. * correct_cls / length_cls acc_epoch_cls += accuracy_cls.item() acc_epoch_cls /= len(train_loader) loss_epoch /= len(train_loader) if acc_epoch_cls>acc_max: acc_max = acc_epoch_cls epoch_max = epoch early_stopping(acc_epoch_cls, self.backbone) if early_stopping.early_stop: print("Early stopping") break if (epoch+1)%opt.save_freq==0: print("[INFO] save backbone at epoch {}!".format(epoch)) torch.save(self.backbone.state_dict(), '{}/backbone_{}.tar'.format(opt.ckpt_dir, epoch)) print('Epoch [{}][{}][{}] loss= {:.5f}; Epoch ACC.= {:.2f}%, CLS.= {:.2f}%, ' 'Max ACC.= {:.1f}%, Max Epoch={}' \ .format(epoch + 1, opt.model_name, opt.dataset_name, loss_epoch, acc_epoch,acc_epoch_cls, acc_max, epoch_max)) return acc_max, epoch_max class RelationalReasoning_InterIntra(torch.nn.Module): def __init__(self, backbone, feature_size=64, nb_class=3): super(RelationalReasoning_InterIntra, self).__init__() self.backbone = backbone self.relation_head = torch.nn.Sequential( torch.nn.Linear(feature_size*2, 256), torch.nn.BatchNorm1d(256), torch.nn.LeakyReLU(), torch.nn.Linear(256, 1)) self.cls_head = torch.nn.Sequential( torch.nn.Linear(feature_size*2, 256), torch.nn.BatchNorm1d(256), torch.nn.LeakyReLU(), torch.nn.Linear(256, nb_class), torch.nn.Softmax(), ) # self.softmax = nn.Softmax() def aggregate(self, features, K): relation_pairs_list = list() targets_list = list() size = int(features.shape[0] / K) shifts_counter=1 for index_1 in range(0, size*K, size): for index_2 in range(index_1+size, size*K, size): # Using the 'cat' aggregation function by default pos1 = features[index_1:index_1 + size] pos2 = features[index_2:index_2+size] pos_pair = torch.cat([pos1, pos2], 1) # (batch_size, fz*2) # Shuffle without collisions by rolling the mini-batch (negatives) neg1 = torch.roll(features[index_2:index_2 + size], shifts=shifts_counter, dims=0) neg_pair1 = torch.cat([pos1, neg1], 1) # (batch_size, fz*2) relation_pairs_list.append(pos_pair) relation_pairs_list.append(neg_pair1) targets_list.append(torch.ones(size, dtype=torch.float32).cuda()) targets_list.append(torch.zeros(size, dtype=torch.float32).cuda()) shifts_counter+=1 if(shifts_counter>=size): shifts_counter=1 # avoid identity pairs relation_pairs = torch.cat(relation_pairs_list, 0).cuda() # K(K-1) * (batch_size, fz*2) targets = torch.cat(targets_list, 0).cuda() return relation_pairs, targets def run_test(self, predict, labels): correct = 0 pred = predict.data.max(1)[1] correct = pred.eq(labels.data).cpu().sum() return correct, len(labels.data) def train(self, tot_epochs, train_loader, opt): patience = opt.patience early_stopping = EarlyStopping(patience, verbose=True, checkpoint_pth='{}/backbone_best.tar'.format(opt.ckpt_dir)) optimizer = torch.optim.Adam([ {'params': self.backbone.parameters()}, {'params': self.relation_head.parameters()}, {'params': self.cls_head.parameters()}, ], lr=opt.learning_rate) BCE = torch.nn.BCEWithLogitsLoss() c_criterion = nn.CrossEntropyLoss() self.backbone.train() self.relation_head.train() self.cls_head.train() epoch_max = 0 acc_max=0 for epoch in range(tot_epochs): acc_epoch=0 acc_epoch_cls=0 loss_epoch=0 # the real target is discarded (unsupervised) for i, (data, data_augmented0, data_augmented1, data_label, _) in enumerate(train_loader): K = len(data) # tot augmentations x = torch.cat(data, 0).cuda() x_cut0 = torch.cat(data_augmented0, 0).cuda() x_cut1 = torch.cat(data_augmented1, 0).cuda() c_label = torch.cat(data_label, 0).cuda() optimizer.zero_grad() # forward pass (backbone) features = self.backbone(x) features_cut0 = self.backbone(x_cut0) features_cut1 = self.backbone(x_cut1) features_cls = torch.cat([features_cut0, features_cut1], 1) # aggregation function relation_pairs, targets = self.aggregate(features, K) # relation_pairs_intra, targets_intra = self.aggregate_intra(features_cut0, features_cut1, K) # forward pass (relation head) score = self.relation_head(relation_pairs).squeeze() c_output = self.cls_head(features_cls) correct_cls, length_cls = self.run_test(c_output, c_label) # cross-entropy loss and backward loss = BCE(score, targets) loss_c = c_criterion(c_output, c_label) loss+=loss_c loss.backward() optimizer.step() # estimate the accuracy predicted = torch.round(torch.sigmoid(score)) correct = predicted.eq(targets.view_as(predicted)).sum() accuracy = (100.0 * correct / float(len(targets))) acc_epoch += accuracy.item() loss_epoch += loss.item() accuracy_cls = 100. * correct_cls / length_cls acc_epoch_cls += accuracy_cls.item() acc_epoch /= len(train_loader) acc_epoch_cls /= len(train_loader) loss_epoch /= len(train_loader) if (acc_epoch+acc_epoch_cls)>acc_max: acc_max = (acc_epoch+acc_epoch_cls) epoch_max = epoch early_stopping((acc_epoch+acc_epoch_cls), self.backbone) if early_stopping.early_stop: print("Early stopping") break if (epoch+1)%opt.save_freq==0: print("[INFO] save backbone at epoch {}!".format(epoch)) torch.save(self.backbone.state_dict(), '{}/backbone_{}.tar'.format(opt.ckpt_dir, epoch)) print('Epoch [{}][{}][{}] loss= {:.5f}; Epoch ACC.= {:.2f}%, CLS.= {:.2f}%, ' 'Max ACC.= {:.1f}%, Max Epoch={}' \ .format(epoch + 1, opt.model_name, opt.dataset_name, loss_epoch, acc_epoch,acc_epoch_cls, acc_max, epoch_max)) return acc_max, epoch_max

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null

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null

0

7

a2a4519512eac204e954f202e7af1ccff6bb708b

2,053

py

Python

python/tvm/relay/op/reduce.py

gaoxiong1/tvm

6770f6b77252cf17a89ea7aeb292a2a54190cfff

[ "Apache-2.0" ]

null

python/tvm/relay/op/reduce.py

gaoxiong1/tvm

6770f6b77252cf17a89ea7aeb292a2a54190cfff

[ "Apache-2.0" ]

null

python/tvm/relay/op/reduce.py

gaoxiong1/tvm

6770f6b77252cf17a89ea7aeb292a2a54190cfff

[ "Apache-2.0" ]

null

"""Reduce operators.""" # pylint: disable=redefined-builtin from . import _make def argmax(data, axis=None, keepdims=False, exclude=False): """Returns the indices of the maximum values along an axis. Parameters ---------- data : relay.Expr The input data axis : None or int or tuple of int Axis or axes along which a argmin operation is performed. The default, axis=None, will find the indices of maximum element all of the elements of the input array. If axis is negative it counts from the last to the first axis. keepdims : bool If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. exclude : bool If `exclude` is true, reduction will be performed on the axes that are NOT in axis instead. Returns ------- result : relay.Expr The computed result. """ return _make.argmax(data, axis, keepdims, exclude) def argmin(data, axis=None, keepdims=False, exclude=False): """Returns the indices of the minimum values along an axis. Parameters ---------- data : relay.Expr The input data axis : None or int or tuple of int Axis or axes along which a argmin operation is performed. The default, axis=None, will find the indices of minimum element all of the elements of the input array. If axis is negative it counts from the last to the first axis. keepdims : bool If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. exclude : bool If `exclude` is true, reduction will be performed on the axes that are NOT in axis instead. Returns ------- result : relay.Expr The computed result. """ return _make.argmin(data, axis, keepdims, exclude)

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a2ca122fdf88b843e6d3c5f4128d47846d4a9d74

11,455

py

Python

api/response_modifiers.py

clearspending/api.clearspending.ru

ece8f9f5f1b37598cf12ad67e2a6da6214afc27c

[ "MIT" ]

1

2019-01-15T16:52:58.000Z

api/response_modifiers.py

clearspending/api.clearspending.ru

ece8f9f5f1b37598cf12ad67e2a6da6214afc27c

[ "MIT" ]

null

api/response_modifiers.py

clearspending/api.clearspending.ru

ece8f9f5f1b37598cf12ad67e2a6da6214afc27c

[ "MIT" ]

null

# coding=utf-8 def modifier_select_rsp_contracts(parametersDict): ''' модификатор входных параметров апи для коллекции контрактов ''' maxResultsPerQuery = 50 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage returnfields = { "_id": 1, "id": 1, "regNum": 1, "price": 1, "signDate": 1, "customer.fullName": 1, "customer.inn": 1, "customer.kpp": 1, "customer.regNum": 1, "products": 1, "fz": 1, "regionCode": 1, "suppliers": 1, "misuses": 1, "finances.budgetary": 1, 'name': 1, "publishDate": 1, 'economic_sectors': 1 } try: parametersDict["supplierinn"] = parametersDict["supplierinn"].replace("%20", " ") except: pass try: parametersDict["supplierkpp"] = parametersDict["supplierkpp"].replace("%20", " ") except: pass if parametersDict.get("returnfields", None) == None: parametersDict["returnfields"] = returnfields else: pass return parametersDict def modifier_select_rsp_notifications(parametersDict): ''' модификатор входных параметров апи для коллекции контрактов ''' maxResultsPerQuery = 50 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage if parametersDict.get("returnfields", None): parametersDict["returnfields"] = { "number": 1, "placingWay": 1, "orderName": 1, "lots": 1, 'lot': 1, 'regionCode': 1, "publishDate": 1, "notificationCommission": 1, "contactInfo": 1, "href": 1, "documentMetas": 1 } return parametersDict def modifier_select_rsp_grants(parametersDict): ''' модификатор входных параметров апи для коллекции контрактов ''' maxResultsPerQuery = 50 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage if parametersDict.get("returnfields", None): parametersDict["returnfields"] = { "name_organization": 1, "status": 1, "grant_status": 1, "description": 1, "grant": 1, "price": 1, "site": 1, "OGRN": 1, "filing_date": 1, "form_number": 1, "address": 1, "operator": 1, "name_project": 1, } return parametersDict def modifier_select_rsp_invalidcontracts(parametersDict): ''' модификатор входных параметров апи для коллекции контрактов с проблемными инн/кпп ''' maxResultsPerQuery = 50 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage try: parametersDict["supplierinn"] = parametersDict["supplierinn"].replace("%20", " ") except: pass try: parametersDict["supplierkpp"] = parametersDict["supplierkpp"].replace("%20", " ") except: pass return parametersDict def modifier_select_rsp_customers(parametersDict): ''' модификатор входных параметров апи для коллекции заказчиков ''' maxResultsPerQuery = 50 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage returnfields = { "_id": 1, "id": 1, "regNumber": 1, "fullName": 1, "inn": 1, "kpp": 1, "contractsSum": 1, "contractsCount": 1, "_orgClass": 1 } if parametersDict.get("returnfields", None) == None: parametersDict["returnfields"] = returnfields else: pass return parametersDict def modifier_select_rsp_suppliers(parametersDict): ''' модификатор входных параметров апи для коллекции поставщиков ''' maxResultsPerQuery = 50 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage try: parametersDict["inn"] = parametersDict["inn"].replace("%20", " ") except: pass try: parametersDict["kpp"] = parametersDict["kpp"].replace("%20", " ") except: pass return parametersDict def modifier_select_rsp_dictionaries(parametersDict): ''' модификатор входных параметров апи для коллекций справочников ''' maxResultsPerQuery = 1000 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage return parametersDict def modifier_get_notifications_rsp(parametersDict): if not parametersDict.get("returnfields", None): parametersDict["returnfields"] = { "number": 1, "placingWay": 1, "orderName": 1, 'purchaseObjectInfo': 1, 'purchaseResponsible': 1, 'procedureInfo': 1, "lots": 1, 'lot': 1, 'fz': 1, "publishDate": 1, 'regionCode': 1, "notificationCommission": 1, "contactInfo": 1, "href": 1, "documentMetas": 1, 'customers': 1, } return parametersDict def modifier_get_grants_rsp(parametersDict): if not parametersDict.get("returnfields", None): parametersDict["returnfields"] = { "name_organization": 1, "status": 1, "grant_status": 1, "description": 1, "grant": 1, "price": 1, "site": 1, "OGRN": 1, "filing_date": 1, "form_number": 1, "address": 1, "operator": 1, "name_project": 1, } return parametersDict def modifier_get_rsp(parametersDict): ''' модификатор входных параметров апи всех get-запросов ''' parametersDict["perpage"] = 1 try: parametersDict["supplierinn"] = parametersDict["supplierinn"].replace("%20", " ") except: pass try: parametersDict["supplierkpp"] = parametersDict["supplierkpp"].replace("%20", " ") except: pass try: parametersDict["inn"] = parametersDict["inn"].replace("%20", " ") except: pass try: parametersDict["kpp"] = parametersDict["kpp"].replace("%20", " ") except: pass return parametersDict def modifier_top_rsp_contracts(parametersDict): ''' модификатор входных параметров апи для коллекции топ контрактов ''' maxResultsPerQuery = 100 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage returnfields = { "year": 1, "regNum": 1, "price": 1, "signDate": 1, "customer.fullName": 1, "customer.inn": 1, "customer.kpp": 1, "customer.regNum": 1, "regionCode": 1, "products": 1, "suppliers": 1 } if parametersDict.get("returnfields", None) == None: parametersDict["returnfields"] = returnfields else: pass return parametersDict def modifier_top_rsp_notifications(parametersDict): ''' модификатор входных параметров апи для коллекции топ контрактов ''' maxResultsPerQuery = 100 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage if parametersDict.get("returnfields", None): parametersDict["returnfields"] = { "number": 1, "placingWay": 1, "orderName": 1, "lots": 1, 'lot': 1, 'regionCode': 1, "publishDate": 1, "notificationCommission": 1, "contactInfo": 1, "href": 1, "documentMetas": 1, } return parametersDict def modifier_top_rsp_grants(parametersDict): ''' модификатор входных параметров апи для коллекции топ контрактов ''' maxResultsPerQuery = 100 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage if parametersDict.get("returnfields", None): parametersDict["returnfields"] = { "name_organization": 1, "status": 1, "grant_status": 1, "description": 1, "grant": 1, "price": 1, "site": 1, "OGRN": 1, "filing_date": 1, "form_number": 1, "address": 1, "operator": 1, "name_project": 1, } return parametersDict def modifier_top_rsp_organizations(parametersDict): ''' модификатор входных параметров апи для коллекции топ заказчиков и поставщиков ''' maxResultsPerQuery = 100 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage returnfields = {u"_id": 0} if parametersDict.get("returnfields", None) == None: parametersDict["returnfields"] = returnfields else: pass return parametersDict def modifier_top_rsp_farma(parametersDict): ''' модификатор входных параметров апи для коллекции топ заказчиков и поставщиков ''' maxResultsPerQuery = 100 try: perpage = int(parametersDict.get("perpage", maxResultsPerQuery)) except: perpage = maxResultsPerQuery if perpage > maxResultsPerQuery or perpage == 0: perpage = maxResultsPerQuery parametersDict["perpage"] = perpage if not parametersDict.get("returnfields", None): parametersDict["returnfields"] = { "_id": 0, "name": 1, "share": 1, "summ": 1, "inn": 1, "num": 1, } return parametersDict

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1

0

1

0

null

0

7

0c050caeea403f34df6fd62e8421208888e77566

503

py

Python

functions_make_shirt_anthro_club.py

julencosme/python-crash-course

6b37d7346e235273c266110932207cd67ce4eb0e

[ "MIT" ]

null

functions_make_shirt_anthro_club.py

julencosme/python-crash-course

6b37d7346e235273c266110932207cd67ce4eb0e

[ "MIT" ]

null

functions_make_shirt_anthro_club.py

julencosme/python-crash-course

6b37d7346e235273c266110932207cd67ce4eb0e

[ "MIT" ]

null

def make_shirt(size, message): """Display information regarding the size and message of a shirt.""" print("The shirt size is " + size + " and the message will read: " + message + ".") make_shirt('large', 'Archaeology Club') def make_shirt(size, message): """Display information regarding the size and message of a shirt.""" print("The shirt size is " + size + " and the message will read: " + message + ".") make_shirt(size='large', message='Archaeology Club')

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null

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8

0c05ddf647aeb0272d2db1a00c2076be2092ee9b

19,412

py

Python

tests/test_managedblockchain/test_managedblockchain_nodes.py

orenmazor/moto

4778377e8ecaf729d26602a2c5202b72c1438503

[ "Apache-2.0" ]

null

tests/test_managedblockchain/test_managedblockchain_nodes.py

orenmazor/moto

4778377e8ecaf729d26602a2c5202b72c1438503

[ "Apache-2.0" ]

4

2017-09-30T07:52:52.000Z

2021-12-13T06:56:55.000Z

tests/test_managedblockchain/test_managedblockchain_nodes.py

orenmazor/moto

4778377e8ecaf729d26602a2c5202b72c1438503

[ "Apache-2.0" ]

2

2021-11-24T08:05:43.000Z

2021-11-25T16:18:48.000Z

from __future__ import unicode_literals import boto3 import pytest import sure # noqa from botocore.exceptions import ClientError from moto import mock_managedblockchain from . import helpers @mock_managedblockchain def test_create_node(): conn = boto3.client("managedblockchain", region_name="us-east-1") # Create network response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] member_id = response["MemberId"] # Create a node response = conn.create_node( NetworkId=network_id, MemberId=member_id, NodeConfiguration=helpers.default_nodeconfiguration, ) node_id = response["NodeId"] # Find node in full list response = conn.list_nodes(NetworkId=network_id, MemberId=member_id) nodes = response["Nodes"] nodes.should.have.length_of(1) helpers.node_id_exist_in_list(nodes, node_id).should.equal(True) # Get node details response = conn.get_node(NetworkId=network_id, MemberId=member_id, NodeId=node_id) response["Node"]["AvailabilityZone"].should.equal("us-east-1a") # Update node logconfignewenabled = not helpers.default_nodeconfiguration[ "LogPublishingConfiguration" ]["Fabric"]["ChaincodeLogs"]["Cloudwatch"]["Enabled"] logconfignew = { "Fabric": {"ChaincodeLogs": {"Cloudwatch": {"Enabled": logconfignewenabled}}} } conn.update_node( NetworkId=network_id, MemberId=member_id, NodeId=node_id, LogPublishingConfiguration=logconfignew, ) # Delete node conn.delete_node( NetworkId=network_id, MemberId=member_id, NodeId=node_id, ) # Find node in full list response = conn.list_nodes(NetworkId=network_id, MemberId=member_id) nodes = response["Nodes"] nodes.should.have.length_of(1) helpers.node_id_exist_in_list(nodes, node_id).should.equal(True) # Find node in full list - only DELETED response = conn.list_nodes( NetworkId=network_id, MemberId=member_id, Status="DELETED" ) nodes = response["Nodes"] nodes.should.have.length_of(1) helpers.node_id_exist_in_list(nodes, node_id).should.equal(True) # But cannot get with pytest.raises(ClientError) as ex: conn.get_node(NetworkId=network_id, MemberId=member_id, NodeId=node_id) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Node {0} not found".format(node_id)) @mock_managedblockchain def test_create_node_standard_edition(): conn = boto3.client("managedblockchain", region_name="us-east-1") frameworkconfiguration = {"Fabric": {"Edition": "STANDARD"}} response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] member_id = response["MemberId"] # Instance type only allowed with standard edition logconfigbad = dict(helpers.default_nodeconfiguration) logconfigbad["InstanceType"] = "bc.t3.large" response = conn.create_node( NetworkId=network_id, MemberId=member_id, NodeConfiguration=logconfigbad, ) node_id = response["NodeId"] # Get node details response = conn.get_node(NetworkId=network_id, MemberId=member_id, NodeId=node_id) response["Node"]["InstanceType"].should.equal("bc.t3.large") # Need another member so the network does not get deleted # Create proposal response = conn.create_proposal( NetworkId=network_id, MemberId=member_id, Actions=helpers.default_policy_actions, ) proposal_id = response["ProposalId"] # Vote yes response = conn.vote_on_proposal( NetworkId=network_id, ProposalId=proposal_id, VoterMemberId=member_id, Vote="YES", ) # Get the invitation response = conn.list_invitations() invitation_id = response["Invitations"][0]["InvitationId"] # Create the member response = conn.create_member( InvitationId=invitation_id, NetworkId=network_id, MemberConfiguration=helpers.create_member_configuration( "testmember2", "admin", "Admin12345", False, "Test Member 2" ), ) # Remove member 1 - should remove nodes conn.delete_member(NetworkId=network_id, MemberId=member_id) # Should now be an exception with pytest.raises(ClientError) as ex: conn.list_nodes(NetworkId=network_id, MemberId=member_id) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Member {0} not found".format(member_id)) @mock_managedblockchain def test_create_too_many_nodes(): conn = boto3.client("managedblockchain", region_name="us-east-1") # Create network response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] member_id = response["MemberId"] # Create a node response = conn.create_node( NetworkId=network_id, MemberId=member_id, NodeConfiguration=helpers.default_nodeconfiguration, ) # Create another node response = conn.create_node( NetworkId=network_id, MemberId=member_id, NodeConfiguration=helpers.default_nodeconfiguration, ) # Find node in full list response = conn.list_nodes(NetworkId=network_id, MemberId=member_id) nodes = response["Nodes"] nodes.should.have.length_of(2) # Try to create one too many nodes with pytest.raises(ClientError) as ex: conn.create_node( NetworkId=network_id, MemberId=member_id, NodeConfiguration=helpers.default_nodeconfiguration, ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceLimitExceededException") err["Message"].should.contain( "Maximum number of nodes exceeded in member {0}".format(member_id) ) @mock_managedblockchain def test_create_node_badnetwork(): conn = boto3.client("managedblockchain", region_name="us-east-1") with pytest.raises(ClientError) as ex: conn.create_node( NetworkId="n-ABCDEFGHIJKLMNOP0123456789", MemberId="m-ABCDEFGHIJKLMNOP0123456789", NodeConfiguration=helpers.default_nodeconfiguration, ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Network n-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_create_node_badmember(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] with pytest.raises(ClientError) as ex: conn.create_node( NetworkId=network_id, MemberId="m-ABCDEFGHIJKLMNOP0123456789", NodeConfiguration=helpers.default_nodeconfiguration, ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Member m-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_create_node_badnodeconfig(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] member_id = response["MemberId"] # Incorrect instance type logconfigbad = dict(helpers.default_nodeconfiguration) logconfigbad["InstanceType"] = "foo" with pytest.raises(ClientError) as ex: conn.create_node( NetworkId=network_id, MemberId=member_id, NodeConfiguration=logconfigbad ) err = ex.value.response["Error"] err["Code"].should.equal("InvalidRequestException") err["Message"].should.contain("Requested instance foo isn't supported.") # Incorrect instance type for edition logconfigbad = dict(helpers.default_nodeconfiguration) logconfigbad["InstanceType"] = "bc.t3.large" with pytest.raises(ClientError) as ex: conn.create_node( NetworkId=network_id, MemberId=member_id, NodeConfiguration=logconfigbad ) err = ex.value.response["Error"] err["Code"].should.equal("InvalidRequestException") err["Message"].should.contain( "Instance type bc.t3.large is not supported with STARTER Edition networks." ) # Incorrect availability zone logconfigbad = dict(helpers.default_nodeconfiguration) logconfigbad["AvailabilityZone"] = "us-east-11" with pytest.raises(ClientError) as ex: conn.create_node( NetworkId=network_id, MemberId=member_id, NodeConfiguration=logconfigbad ) err = ex.value.response["Error"] err["Code"].should.equal("InvalidRequestException") err["Message"].should.contain("Availability Zone is not valid") @mock_managedblockchain def test_list_nodes_badnetwork(): conn = boto3.client("managedblockchain", region_name="us-east-1") with pytest.raises(ClientError) as ex: conn.list_nodes( NetworkId="n-ABCDEFGHIJKLMNOP0123456789", MemberId="m-ABCDEFGHIJKLMNOP0123456789", ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Network n-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_list_nodes_badmember(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] with pytest.raises(ClientError) as ex: conn.list_nodes( NetworkId=network_id, MemberId="m-ABCDEFGHIJKLMNOP0123456789", ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Member m-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_get_node_badnetwork(): conn = boto3.client("managedblockchain", region_name="us-east-1") with pytest.raises(ClientError) as ex: conn.get_node( NetworkId="n-ABCDEFGHIJKLMNOP0123456789", MemberId="m-ABCDEFGHIJKLMNOP0123456789", NodeId="nd-ABCDEFGHIJKLMNOP0123456789", ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Network n-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_get_node_badmember(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] with pytest.raises(ClientError) as ex: conn.get_node( NetworkId=network_id, MemberId="m-ABCDEFGHIJKLMNOP0123456789", NodeId="nd-ABCDEFGHIJKLMNOP0123456789", ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Member m-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_get_node_badnode(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] member_id = response["MemberId"] with pytest.raises(ClientError) as ex: conn.get_node( NetworkId=network_id, MemberId=member_id, NodeId="nd-ABCDEFGHIJKLMNOP0123456789", ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Node nd-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_delete_node_badnetwork(): conn = boto3.client("managedblockchain", region_name="us-east-1") with pytest.raises(ClientError) as ex: conn.delete_node( NetworkId="n-ABCDEFGHIJKLMNOP0123456789", MemberId="m-ABCDEFGHIJKLMNOP0123456789", NodeId="nd-ABCDEFGHIJKLMNOP0123456789", ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Network n-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_delete_node_badmember(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] with pytest.raises(ClientError) as ex: conn.delete_node( NetworkId=network_id, MemberId="m-ABCDEFGHIJKLMNOP0123456789", NodeId="nd-ABCDEFGHIJKLMNOP0123456789", ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Member m-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_delete_node_badnode(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] member_id = response["MemberId"] with pytest.raises(ClientError) as ex: conn.delete_node( NetworkId=network_id, MemberId=member_id, NodeId="nd-ABCDEFGHIJKLMNOP0123456789", ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Node nd-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_update_node_badnetwork(): conn = boto3.client("managedblockchain", region_name="us-east-1") with pytest.raises(ClientError) as ex: conn.update_node( NetworkId="n-ABCDEFGHIJKLMNOP0123456789", MemberId="m-ABCDEFGHIJKLMNOP0123456789", NodeId="nd-ABCDEFGHIJKLMNOP0123456789", LogPublishingConfiguration=helpers.default_nodeconfiguration[ "LogPublishingConfiguration" ], ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Network n-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_update_node_badmember(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] with pytest.raises(ClientError) as ex: conn.update_node( NetworkId=network_id, MemberId="m-ABCDEFGHIJKLMNOP0123456789", NodeId="nd-ABCDEFGHIJKLMNOP0123456789", LogPublishingConfiguration=helpers.default_nodeconfiguration[ "LogPublishingConfiguration" ], ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Member m-ABCDEFGHIJKLMNOP0123456789 not found") @mock_managedblockchain def test_update_node_badnode(): conn = boto3.client("managedblockchain", region_name="us-east-1") response = conn.create_network( Name="testnetwork1", Description="Test Network 1", Framework="HYPERLEDGER_FABRIC", FrameworkVersion="1.2", FrameworkConfiguration=helpers.default_frameworkconfiguration, VotingPolicy=helpers.default_votingpolicy, MemberConfiguration=helpers.default_memberconfiguration, ) network_id = response["NetworkId"] member_id = response["MemberId"] with pytest.raises(ClientError) as ex: conn.update_node( NetworkId=network_id, MemberId=member_id, NodeId="nd-ABCDEFGHIJKLMNOP0123456789", LogPublishingConfiguration=helpers.default_nodeconfiguration[ "LogPublishingConfiguration" ], ) err = ex.value.response["Error"] err["Code"].should.equal("ResourceNotFoundException") err["Message"].should.contain("Node nd-ABCDEFGHIJKLMNOP0123456789 not found")

35.23049

86

0.69797

1,917

19,412

6.90506

0.083464

0.052882

0.040795

0.054997

0.878296

0.876936

0.858956

0.848531

0.841278

0.832968

0

0.030542

0.197146

19,412

550

87

35.294545

0.8188

0.031733

0

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0

0.207641

0.086637

0

1

0.038724

false

0

0.015945

0

0.05467

0

null

0

1

0

1

0

null

0

7

0c5b11eb1d09d9cb3dfddbdeede503e0411a5198

136

py

Python

slot_attention/__init__.py

ajabri/slot-attention

32acb6614f1bd511f2dc3c263f852ed2dbe9c213

[ "MIT" ]

247

2020-06-29T19:08:50.000Z

2022-03-30T08:36:24.000Z

slot_attention/__init__.py

ajabri/slot-attention

32acb6614f1bd511f2dc3c263f852ed2dbe9c213

[ "MIT" ]

7

2020-07-01T01:32:49.000Z

2021-02-01T20:13:49.000Z

slot_attention/__init__.py

ajabri/slot-attention

32acb6614f1bd511f2dc3c263f852ed2dbe9c213

[ "MIT" ]

26

2020-07-01T00:55:45.000Z

2022-03-25T12:05:24.000Z

from slot_attention.slot_attention import SlotAttention from slot_attention.slot_attention_experimental import SlotAttentionExperimental

68

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0.933824

15

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8.133333

0.466667

0.42623

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0.344262

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0

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1

0

8

a7828daa74d1c8d8c37d01305c8089247a3d54d4

13,717

py

Python

Visualizer/Source/Visualizer/ControlledDataSet.py

NB4444/BachelorProjectEnergyManager

d1fd93dcc83af6d6acd36b7efda364ac2aab90eb

[ "MIT" ]

null

Visualizer/Source/Visualizer/ControlledDataSet.py

NB4444/BachelorProjectEnergyManager

d1fd93dcc83af6d6acd36b7efda364ac2aab90eb

[ "MIT" ]

null

Visualizer/Source/Visualizer/ControlledDataSet.py

NB4444/BachelorProjectEnergyManager

d1fd93dcc83af6d6acd36b7efda364ac2aab90eb

[ "MIT" ]

null

import collections from enum import Enum from matplotlib import pyplot from typing import Any, OrderedDict from Visualizer.DataSet import DataSet from Visualizer.Plotting.Plot import Plot from Visualizer.Plotting.ScatterPlot import ScatterPlot class ControlComparison(Enum): MEAN = 0 MEDIAN = 1 OPTIMAL = 2 class ControlledDataSet(object): def __init__(self, data_set: DataSet, control_data_set: DataSet): self.data_set = data_set self.control_data_set = control_data_set def energy_savings_vs_runtime_increase(self, control_comparison=ControlComparison.MEAN, normalized=True, use_ear=False): control_energy_consumption = None control_runtime = None if control_comparison == ControlComparison.MEAN: control_energy_consumption = self.control_data_set.mean_energy_consumption(use_ear) control_runtime = self.control_data_set.mean_runtime elif control_comparison == ControlComparison.MEDIAN: control_energy_consumption = self.control_data_set.median_energy_consumption(use_ear) control_runtime = self.control_data_set.median_runtime elif control_comparison == ControlComparison.OPTIMAL: control_energy_consumption = self.control_data_set.minimum_energy_consumption_profiler_session.total_energy_consumption( use_ear) control_runtime = self.control_data_set.minimum_runtime_profiler_session.total_runtime data: OrderedDict[str, OrderedDict[Any, Any]] = collections.OrderedDict({}) for profiler_session in self.data_set.data: energy_savings = control_energy_consumption - profiler_session.total_energy_consumption(use_ear) runtime_increase = profiler_session.total_runtime - control_runtime profile = "Runs" if profile not in data: data[profile] = collections.OrderedDict() if normalized: data[profile][ runtime_increase / control_runtime * 100] = energy_savings / control_energy_consumption * 100 else: data[profile][Plot.ns_to_s(runtime_increase)] = energy_savings return data def energy_savings_vs_runtime_increase_plot(self, control_comparison=ControlComparison.MEAN, normalized=True, use_ear=False): plot_series = self.energy_savings_vs_runtime_increase(control_comparison, normalized) values = [] for profiler_session in self.data_set.data: if "maximumCPUClockRate" in profiler_session.profile: values.append( profiler_session.profile["maximumCPUClockRate"] + profiler_session.profile["maximumGPUClockRate"]) max_value = max(values, default=None) min_value = min(values, default=None) return ScatterPlot( title="Energy Savings vs. Runtime Increase", plot_series=plot_series, x_label="Runtime Increase (" + ("% of optimal" if normalized else "Seconds") + ")", y_label="Energy Savings (" + ("% of optimal" if normalized else "Joules") + ")", colors=[pyplot.get_cmap("gist_rainbow")((value - min_value) / (max_value - min_value)) for value in values] if len(values) > 0 else None, labels=[profiler_session.plot_label(use_ear) for profiler_session in self.data_set.data] ) def energy_savings_vs_flops_decrease(self, control_comparison=ControlComparison.MEAN, normalized=True, use_ear=False): control_energy_consumption = None control_flops = None if control_comparison == ControlComparison.MEAN: control_energy_consumption = self.control_data_set.mean_energy_consumption(use_ear) control_flops = self.control_data_set.mean_flops elif control_comparison == ControlComparison.MEDIAN: control_energy_consumption = self.control_data_set.median_energy_consumption(use_ear) control_flops = self.control_data_set.median_flops elif control_comparison == ControlComparison.OPTIMAL: control_energy_consumption = self.control_data_set.minimum_energy_consumption_profiler_session.total_energy_consumption( use_ear) control_flops = self.control_data_set.maximum_flops_profiler_session.total_flops data: OrderedDict[str, OrderedDict[Any, Any]] = collections.OrderedDict({}) for profiler_session in self.data_set.data: energy_savings = control_energy_consumption - profiler_session.total_energy_consumption(use_ear) flops_decrease = control_flops - profiler_session.total_flops profile = "Runs" if profile not in data: data[profile] = collections.OrderedDict() if normalized: data[profile][flops_decrease / control_flops * 100] = energy_savings / control_energy_consumption * 100 else: data[profile][flops_decrease] = energy_savings return data def energy_savings_vs_flops_decrease_plot(self, control_comparison=ControlComparison.MEAN, normalized=True, use_ear=False): plot_series = self.energy_savings_vs_flops_decrease(control_comparison, normalized) values = [] for profiler_session in self.data_set.data: if "maximumCPUClockRate" in profiler_session.profile: values.append( profiler_session.profile["maximumCPUClockRate"] + profiler_session.profile["maximumGPUClockRate"]) max_value = max(values, default=None) min_value = min(values, default=None) return ScatterPlot( title="Energy Savings vs. FLOPs Decrease", plot_series=plot_series, x_label="FLOPs Decrease (" + ("% of optimal" if normalized else "Operations") + ")", y_label="Energy Savings (" + ("% of optimal" if normalized else "Joules") + ")", colors=[pyplot.get_cmap("gist_rainbow")((value - min_value) / (max_value - min_value)) for value in values] if len(values) > 0 else None, labels=[profiler_session.plot_label(use_ear) for profiler_session in self.data_set.data] ) def core_clock_rate_vs_gpu_clock_rate_vs_energy_savings(self, control_comparison=ControlComparison.MEAN, use_ear=False): control_energy_consumption = None if control_comparison == ControlComparison.MEAN: control_energy_consumption = self.control_data_set.mean_energy_consumption(use_ear) elif control_comparison == ControlComparison.MEDIAN: control_energy_consumption = self.control_data_set.median_energy_consumption(use_ear) elif control_comparison == ControlComparison.OPTIMAL: control_energy_consumption = self.control_data_set.minimum_energy_consumption_profiler_session.total_energy_consumption( use_ear) data: OrderedDict[ str, OrderedDict[int, OrderedDict[int, int]]] = collections.OrderedDict({}) for profiler_session in self.data_set.data: savings = control_energy_consumption - profiler_session.total_energy_consumption(use_ear) profile = "Saves Energy" if savings >= 0 else "Costs Energy" if profile not in data: data[profile] = collections.OrderedDict() core_clock_rate = profiler_session.profile["maximumCPUClockRate"] if core_clock_rate not in data[profile]: data[profile][core_clock_rate] = collections.OrderedDict() gpu_clock_rate = profiler_session.profile["maximumGPUClockRate"] data[profile][core_clock_rate][gpu_clock_rate] = savings return data def core_clock_rate_vs_gpu_clock_rate_vs_energy_savings_scatter_plot(self, control_comparison=ControlComparison.MEAN, use_ear=False): return ScatterPlot( title="Core Frequency vs. GPU Frequency vs. Energy Savings", plot_series=self.core_clock_rate_vs_gpu_clock_rate_vs_energy_savings(control_comparison), x_label="Core Clock Rate (Hertz)", y_label="GPU Clock Rate (Hertz)", z_label="Energy Savings (Joules)", labels=[profiler_session.plot_label(use_ear) for profiler_session in self.data_set.data] ) def core_clock_rate_vs_gpu_clock_rate_vs_runtime_increase(self, control_comparison=ControlComparison.MEAN): control_runtime = None if control_comparison == ControlComparison.MEAN: control_runtime = self.control_data_set.mean_runtime elif control_comparison == ControlComparison.MEDIAN: control_runtime = self.control_data_set.median_runtime elif control_comparison == ControlComparison.OPTIMAL: control_runtime = self.control_data_set.minimum_runtime_profiler_session.total_runtime data: OrderedDict[ str, OrderedDict[int, OrderedDict[int, int]]] = collections.OrderedDict({}) for profiler_session in self.data_set.data: increase = Plot.ns_to_s(profiler_session.total_runtime - control_runtime) profile = "Saves Time" if increase <= 0 else "Costs Time" if profile not in data: data[profile] = collections.OrderedDict() core_clock_rate = profiler_session.profile["maximumCPUClockRate"] if core_clock_rate not in data[profile]: data[profile][core_clock_rate] = collections.OrderedDict() gpu_clock_rate = profiler_session.profile["maximumGPUClockRate"] data[profile][core_clock_rate][gpu_clock_rate] = increase return data def core_clock_rate_vs_gpu_clock_rate_vs_runtime_increase_scatter_plot(self, control_comparison=ControlComparison.MEAN, use_ear=False): return ScatterPlot( title="Core Frequency vs. GPU Frequency vs. Runtime Increase", plot_series=self.core_clock_rate_vs_gpu_clock_rate_vs_runtime_increase(control_comparison), x_label="Core Clock Rate (Hertz)", y_label="GPU Clock Rate (Hertz)", z_label="Runtime Increase (Seconds)", labels=[profiler_session.plot_label(use_ear) for profiler_session in self.data_set.data] ) def core_clock_rate_vs_gpu_clock_rate_vs_energy_harvests(self, control_comparison=ControlComparison.MEAN, use_ear=False): control_energy_consumption = None if control_comparison == ControlComparison.MEAN: control_energy_consumption = self.control_data_set.mean_energy_consumption(use_ear) elif control_comparison == ControlComparison.MEDIAN: control_energy_consumption = self.control_data_set.median_energy_consumption(use_ear) elif control_comparison == ControlComparison.OPTIMAL: control_energy_consumption = self.control_data_set.minimum_energy_consumption_profiler_session.total_energy_consumption( use_ear) control_runtime = None if control_comparison == ControlComparison.MEAN: control_runtime = self.control_data_set.mean_runtime elif control_comparison == ControlComparison.MEDIAN: control_runtime = self.control_data_set.median_runtime elif control_comparison == ControlComparison.OPTIMAL: control_runtime = self.control_data_set.minimum_runtime_profiler_session.total_runtime data: OrderedDict[ str, OrderedDict[int, OrderedDict[int, int]]] = collections.OrderedDict({}) for profiler_session in self.data_set.data: energy_savings = control_energy_consumption - profiler_session.total_energy_consumption(use_ear) runtime_increase = Plot.ns_to_s(profiler_session.total_runtime - control_runtime) profile = "Harvests Energy" if energy_savings >= 0 and runtime_increase <= 0 else "Costs Energy" if profile not in data: data[profile] = collections.OrderedDict() core_clock_rate = profiler_session.profile["maximumCPUClockRate"] if core_clock_rate not in data[profile]: data[profile][core_clock_rate] = collections.OrderedDict() gpu_clock_rate = profiler_session.profile["maximumGPUClockRate"] data[profile][core_clock_rate][gpu_clock_rate] = energy_savings return data def core_clock_rate_vs_gpu_clock_rate_vs_energy_harvests_scatter_plot(self, control_comparison=ControlComparison.MEAN, use_ear=False): return ScatterPlot( title="Core Frequency vs. GPU Frequency vs. Energy Harvests", plot_series=self.core_clock_rate_vs_gpu_clock_rate_vs_energy_harvests(control_comparison), x_label="Core Clock Rate (Hertz)", y_label="GPU Clock Rate (Hertz)", z_label="Energy Savings (Joules)", labels=[profiler_session.plot_label(use_ear) for profiler_session in self.data_set.data] )

53.582031

132

0.666764

1,479

13,717

5.82691

0.068966

0.078324

0.110466

0.052216

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0.263906

13,717

255

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null

0

1

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1

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null

0

7

a78e2c5f07cdbd4544044f31a7531a598c9e41e9

2,673

py

Python

runner/runs/doom_bots_sweep.py

neevparikh/hierarchical-doom

082f794b9c6101c4e94f15bf4f93c718ee219ea5

[ "MIT" ]

1

2021-11-19T19:39:36.000Z

runner/runs/doom_bots_sweep.py

neevparikh/hierarchical-doom

082f794b9c6101c4e94f15bf4f93c718ee219ea5

[ "MIT" ]

null

runner/runs/doom_bots_sweep.py

neevparikh/hierarchical-doom

082f794b9c6101c4e94f15bf4f93c718ee219ea5

[ "MIT" ]

null

from runner.run_description import RunDescription, Experiment, ParamGrid _params = ParamGrid([ ('seed', [42]), ]) _experiments = [ Experiment( 'bots_128_fs2_wide', 'python -m algorithms.appo.train_appo --env=doom_dwango5_bots_experimental --train_for_seconds=3600000 --algo=APPO --use_rnn=True --gamma=0.995 --env_frameskip=2 --rollout=32 --reward_scale=0.5 --num_workers=18 --num_envs_per_worker=20 --num_policies=1 --ppo_epochs=1 --rollout=32 --recurrence=32 --macro_batch=2048 --batch_size=2048 --res_w=128 --res_h=72 --wide_aspect_ratio=True', _params.generate_params(randomize=False), dict(DOOM_DEFAULT_UDP_PORT=35300), ), Experiment( 'bots_128_fs2_narrow', 'python -m algorithms.appo.train_appo --env=doom_dwango5_bots_experimental --train_for_seconds=3600000 --algo=APPO --use_rnn=True --gamma=0.995 --env_frameskip=2 --rollout=32 --reward_scale=0.5 --num_workers=18 --num_envs_per_worker=20 --num_policies=1 --ppo_epochs=1 --rollout=32 --recurrence=32 --macro_batch=2048 --batch_size=2048 --res_w=128 --res_h=72 --wide_aspect_ratio=False', _params.generate_params(randomize=False), dict(DOOM_DEFAULT_UDP_PORT=40300), ), Experiment( 'bots_128_fs2_wide_adam0.5', 'python -m algorithms.appo.train_appo --env=doom_dwango5_bots_experimental --train_for_seconds=3600000 --algo=APPO --use_rnn=True --gamma=0.995 --env_frameskip=2 --rollout=32 --reward_scale=0.5 --num_workers=18 --num_envs_per_worker=20 --num_policies=1 --ppo_epochs=1 --rollout=32 --recurrence=32 --macro_batch=2048 --batch_size=2048 --res_w=128 --res_h=72 --wide_aspect_ratio=True --adam_beta1=0.5', _params.generate_params(randomize=False), dict(DOOM_DEFAULT_UDP_PORT=45300), ), Experiment( 'bots_128_fs2_narrow_adam0.5', 'python -m algorithms.appo.train_appo --env=doom_dwango5_bots_experimental --train_for_seconds=3600000 --algo=APPO --use_rnn=True --gamma=0.995 --env_frameskip=2 --rollout=32 --reward_scale=0.5 --num_workers=18 --num_envs_per_worker=20 --num_policies=1 --ppo_epochs=1 --rollout=32 --recurrence=32 --macro_batch=2048 --batch_size=2048 --res_w=128 --res_h=72 --wide_aspect_ratio=False --adam_beta1=0.5', _params.generate_params(randomize=False), dict(DOOM_DEFAULT_UDP_PORT=50300), ), ] RUN_DESCRIPTION = RunDescription('doom_bots_v60_sweep', experiments=_experiments, pause_between_experiments=120, use_gpus=4, experiments_per_gpu=1, max_parallel=4)

66.825

409

0.689487

376

2,673

4.545213

0.236702

0.04213

0.039789

0.046811

0.856641

0.798128

0

0.09787

0.174336

2,673

39

410

68.538462

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0.111111

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0.225215

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1

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false

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0.027778

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0.027778

0

null

0

1

0

1

0

null

0

7

3bef4a453b2029d62313a888cfe679efe08c8aae

129

py

Python

examples/dwf/dwf.py

useblocks/dwf

debfb79cecfa57310627c78c4e5c68e21f7c7b6f

[ "CC-BY-4.0" ]

6

2017-11-24T08:47:06.000Z

2021-06-25T12:02:06.000Z

examples/dwf/dwf.py

useblocks/dwf

debfb79cecfa57310627c78c4e5c68e21f7c7b6f

[ "CC-BY-4.0" ]

null

examples/dwf/dwf.py

useblocks/dwf

debfb79cecfa57310627c78c4e5c68e21f7c7b6f

[ "CC-BY-4.0" ]

null

class Tool: pass class Documentation(Tool): pass class Frustration(Tool): pass class Dwf(Documentation, Frustration, Tool): pass

25.8

49

0.79845

17

129

6.058824

0.352941

0.31068

0.378641

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0.108527

129

4

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32.25

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1

0

1

0

null

0

1

0

1

0

7

ce09f4f51a51d6982cdc96bf07737b96c2700aef

4,858

py

Python

exkaldi/function_config.py

luvwinnie/exkaldi

c1149e3c88dfc66084e8a534fd8f4d4d92556d35

[ "Apache-2.0" ]

1

2021-04-02T03:02:14.000Z

exkaldi/function_config.py

luvwinnie/exkaldi

c1149e3c88dfc66084e8a534fd8f4d4d92556d35

[ "Apache-2.0" ]

null

exkaldi/function_config.py

luvwinnie/exkaldi

c1149e3c88dfc66084e8a534fd8f4d4d92556d35

[ "Apache-2.0" ]

null

def configure(name): if name == 'compute_mfcc': return {"--allow-downsample":["false",str], "--allow-upsample":["false",str], "--blackman-coeff":[0.42,float], "--cepstral-lifter":[22,int], "--channel":[-1,int], "--debug-mel":["false",str], "--dither":[1,int], "--energy-floor":[0,int], "--frame-length":[25,int], "--frame-shift":[10,int], "--high-freq":[0,int], "--htk-compat":["false",str], "--low-freq":[20,int], "--max-feature-vectors":[-1,int], "--min-duration":[0,int], "--num-ceps":[13,int], "--num-mel-bins":[23,int], "--output-format":["kaldi",str], "--preemphasis-coefficient":[0.97,float], "--raw-energy":["true",str], "--remove-dc-offset":["true",str], "--round-to-power-of-two":["true",str], "--sample-frequency":[16000,int], "--snip-edges":["false",str], "--subtract-mean":["false",str], "--use-energy":["true",str], "--utt2spk":["",str], "--vtln-high":[-500,int], "--vtln-low":[100,int], "--vtln-map":["",str], "--vtln-warp":[1,int], "--window-type":["povey",str], "--write-utt2dur":["",str] } elif name == 'compute_fbank': return {"--allow-downsample":["false",str], "--allow-upsample":["false",str], "--blackman-coeff":[0.42,float], "--channel":[-1,int], "--debug-mel":["false",str], "--dither":[1,int], "--energy-floor":[0,int], "--frame-length":[25,int], "--frame-shift":[10,int], "--high-freq":[0,int], "--htk-compat":["false",str], "--low-freq":[20,int], "--max-feature-vectors":[-1,int], "--min-duration":[0,int], "--num-mel-bins":[23,int], "--output-format":["kaldi",str], "--preemphasis-coefficient":[0.97,float], "--raw-energy":["true",str], "--remove-dc-offset":["true",str], "--round-to-power-of-two":["true",str], "--sample-frequency":[16000,int], "--snip-edges":["false",str], "--subtract-mean":["false",str], "--use-energy":["true",str], "--use-log-fbank":["true",str], "--use-power":["true",str], "--utt2spk":["",str], "--vtln-high":[-500,int], "--vtln-low":[100,int], "--vtln-map":["",str], "--vtln-warp":[1,int], "--window-type":["povey",str], "--write-utt2dur":["",str] } elif name == 'compute_plp': return {"--allow-downsample":["false",str], "--allow-upsample":["false",str], "--blackman-coeff":[0.42,float], "--cepstral-lifter":[22,int], "--cepstral-scale":[1,int], "--channel":[-1,int], "--compress-factor":[0.33333,float], "--debug-mel":['false',float], "--dither":[1,int], "--energy-floor":[0,int], "--frame-length":[25,int], "--frame-shift":[10,int], "--high-freq":[0,int], "--htk-compat":["false",str], "--low-freq":[20,int], "--lpc-order":[12,int], "--max-feature-vectors":[-1,int], "--min-duration":[0,int], "--num-ceps":[13,int], "--num-mel-bins":[23,int], "--output-format":["kaldi",str], "--preemphasis-coefficient":[0.97,float], "--raw-energy":["true",str], "--remove-dc-offset":["true",str], "--round-to-power-of-two":["true",str], "--sample-frequency":[16000,int], "--snip-edges":["false",str], "--subtract-mean":["false",str], "--use-energy":["true",str], "--utt2spk":["",str], "--vtln-high":[-500,int], "--vtln-low":[100,int], "--vtln-map":["",str], "--vtln-warp":[1,int], "--window-type":["povey",str], "--write-utt2dur":["",str] } elif name == 'compute_spectrogram': return {"--allow-downsample":["false",str], "--allow-upsample":["false",str], "--blackman-coeff":[0.42,float], "--channel":[-1,int], "--dither":[1,int], "--energy-floor":[0,int], "--frame-length":[25,int], "--frame-shift":[10,int], "--max-feature-vectors":[-1,int], "--min-duration":[0,int], "--output-format":["kaldi",str], "--preemphasis-coefficient":[0.97,float], "--raw-energy":["true",str], "--remove-dc-offset":["true",str], "--round-to-power-of-two":["true",str], "--sample-frequency":[16000,int], "--snip-edges":["false",str], "--subtract-mean":["false",str], "--window-type":["povey",str], "--write-utt2dur":["",str] } elif name == 'decode_lattice': return {"--acoustic-scale":[0.1,float], "--allow-partial":["false",str], "--beam":[13,int], "--beam-delta":[0.5,float], "--delta":[0.000976562,float], "--determinize-lattice":["true",str], "--hash-ratio":[2,int], "--lattice-beam":[8,int], "--max-active":[7000,int], "--max-mem":[50000000,int], "--min-active":[200,int], "--minimize":["false",str], "--phone-determinize":["true",str], "--prune-interval":[25,int], "--word-determinize":["true",str], "--word-symbol-table":["",str] } else: return None

31.751634

45

0.520996

595

4,858

4.245378

0.206723

0.072842

0.036025

0.041172

0.811956

0.795724

0

0.042631

0.155002

4,858

152

46

31.960526

0.572716

0

0.768212

0

0.463249

0.061149

0

1

0.006623

false

0

0.046358

0

null

0

1

0

1

0

null

0

7

ce33095d639f433a869a59cf8b5064b41dae7b53

159

py

Python

tests/test_p_7_satz_von_pick.py

techrabbit58/uebung_informatik_vorkurs

e99312ae66ccccd6bfe45bfd3c3f43c01690659c

[ "Unlicense" ]

null

tests/test_p_7_satz_von_pick.py

techrabbit58/uebung_informatik_vorkurs

e99312ae66ccccd6bfe45bfd3c3f43c01690659c

[ "Unlicense" ]

null

tests/test_p_7_satz_von_pick.py

techrabbit58/uebung_informatik_vorkurs

e99312ae66ccccd6bfe45bfd3c3f43c01690659c

[ "Unlicense" ]

null

""" Teste die 'pick()' funktion. """ from tag_2.p_7_satz_von_pick import pick def test_satz_von_pick(): assert pick(innenpunkte=37, randpunkte=42) == 57

17.666667

52

0.716981

26

159

4.076923

0.769231

0.132075

0.207547

0

0.058824

0.144654

159

8

53

19.875

0.720588

0.176101

0

0.333333

1

0.333333

true

0

0.333333

0

0.666667

0

1

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null

0

1

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1

0

null

0

1

0

1

0

1

0

7

02303ee28bd0812092741fb2878896f54f4e827c

35,065

py

Python

stubs/wafregional.py

claytonbrown/troposphere

bf0f1e48b14f578de0221d50f711467ad716ca87

[ "BSD-2-Clause" ]

null

stubs/wafregional.py

claytonbrown/troposphere

bf0f1e48b14f578de0221d50f711467ad716ca87

[ "BSD-2-Clause" ]

null

stubs/wafregional.py

claytonbrown/troposphere

bf0f1e48b14f578de0221d50f711467ad716ca87

[ "BSD-2-Clause" ]

null

from . import AWSObject, AWSProperty from .validators import * from .constants import * # ------------------------------------------- class WAFRegionalByteMatchTuple(AWSProperty): """# ByteMatchTuple - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html", "Properties": { "FieldToMatch": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-fieldtomatch", "Required": true, "Type": "FieldToMatch", "UpdateType": "Mutable" }, "PositionalConstraint": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-positionalconstraint", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" }, "TargetString": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-targetstring", "PrimitiveType": "String", "Required": false, "UpdateType": "Mutable" }, "TargetStringBase64": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-targetstringbase64", "PrimitiveType": "String", "Required": false, "UpdateType": "Mutable" }, "TextTransformation": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-texttransformation", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'TargetString': (basestring, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-targetstring'), 'TargetStringBase64': (basestring, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-targetstringbase64'), 'PositionalConstraint': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-positionalconstraint'), 'TextTransformation': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-texttransformation'), 'FieldToMatch': (FieldToMatch, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-bytematchtuple.html#cfn-wafregional-bytematchset-bytematchtuple-fieldtomatch') } # ------------------------------------------- class WAFRegionalFieldToMatch(AWSProperty): """# FieldToMatch - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-fieldtomatch.html", "Properties": { "Data": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-fieldtomatch.html#cfn-wafregional-bytematchset-fieldtomatch-data", "PrimitiveType": "String", "Required": false, "UpdateType": "Mutable" }, "Type": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-fieldtomatch.html#cfn-wafregional-bytematchset-fieldtomatch-type", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'Type': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-fieldtomatch.html#cfn-wafregional-bytematchset-fieldtomatch-type'), 'Data': (basestring, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-bytematchset-fieldtomatch.html#cfn-wafregional-bytematchset-fieldtomatch-data') } # ------------------------------------------- class WAFRegionalXssMatchTuple(AWSProperty): """# XssMatchTuple - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-xssmatchtuple.html", "Properties": { "FieldToMatch": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-xssmatchtuple.html#cfn-wafregional-xssmatchset-xssmatchtuple-fieldtomatch", "Required": true, "Type": "FieldToMatch", "UpdateType": "Mutable" }, "TextTransformation": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-xssmatchtuple.html#cfn-wafregional-xssmatchset-xssmatchtuple-texttransformation", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'TextTransformation': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-xssmatchtuple.html#cfn-wafregional-xssmatchset-xssmatchtuple-texttransformation'), 'FieldToMatch': (FieldToMatch, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-xssmatchtuple.html#cfn-wafregional-xssmatchset-xssmatchtuple-fieldtomatch') } # ------------------------------------------- class WAFRegionalRule(AWSProperty): """# Rule - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-rule.html", "Properties": { "Action": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-rule.html#cfn-wafregional-webacl-rule-action", "Required": true, "Type": "Action", "UpdateType": "Mutable" }, "Priority": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-rule.html#cfn-wafregional-webacl-rule-priority", "PrimitiveType": "Integer", "Required": true, "UpdateType": "Mutable" }, "RuleId": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-rule.html#cfn-wafregional-webacl-rule-ruleid", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'Action': (Action, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-rule.html#cfn-wafregional-webacl-rule-action'), 'Priority': (positive_integer, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-rule.html#cfn-wafregional-webacl-rule-priority'), 'RuleId': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-rule.html#cfn-wafregional-webacl-rule-ruleid') } # ------------------------------------------- class WAFRegionalIPSetDescriptor(AWSProperty): """# IPSetDescriptor - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-ipset-ipsetdescriptor.html", "Properties": { "Type": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-ipset-ipsetdescriptor.html#cfn-wafregional-ipset-ipsetdescriptor-type", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" }, "Value": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-ipset-ipsetdescriptor.html#cfn-wafregional-ipset-ipsetdescriptor-value", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'Type': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-ipset-ipsetdescriptor.html#cfn-wafregional-ipset-ipsetdescriptor-type'), 'Value': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-ipset-ipsetdescriptor.html#cfn-wafregional-ipset-ipsetdescriptor-value') } # ------------------------------------------- class WAFRegionalFieldToMatch(AWSProperty): """# FieldToMatch - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-fieldtomatch.html", "Properties": { "Data": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-fieldtomatch.html#cfn-wafregional-xssmatchset-fieldtomatch-data", "PrimitiveType": "String", "Required": false, "UpdateType": "Mutable" }, "Type": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-fieldtomatch.html#cfn-wafregional-xssmatchset-fieldtomatch-type", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'Type': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-fieldtomatch.html#cfn-wafregional-xssmatchset-fieldtomatch-type'), 'Data': (basestring, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-xssmatchset-fieldtomatch.html#cfn-wafregional-xssmatchset-fieldtomatch-data') } # ------------------------------------------- class WAFRegionalSizeConstraint(AWSProperty): """# SizeConstraint - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html", "Properties": { "ComparisonOperator": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html#cfn-wafregional-sizeconstraintset-sizeconstraint-comparisonoperator", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" }, "FieldToMatch": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html#cfn-wafregional-sizeconstraintset-sizeconstraint-fieldtomatch", "Required": true, "Type": "FieldToMatch", "UpdateType": "Mutable" }, "Size": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html#cfn-wafregional-sizeconstraintset-sizeconstraint-size", "PrimitiveType": "Integer", "Required": true, "UpdateType": "Mutable" }, "TextTransformation": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html#cfn-wafregional-sizeconstraintset-sizeconstraint-texttransformation", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'ComparisonOperator': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html#cfn-wafregional-sizeconstraintset-sizeconstraint-comparisonoperator'), 'Size': (positive_integer, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html#cfn-wafregional-sizeconstraintset-sizeconstraint-size'), 'TextTransformation': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html#cfn-wafregional-sizeconstraintset-sizeconstraint-texttransformation'), 'FieldToMatch': (FieldToMatch, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-sizeconstraint.html#cfn-wafregional-sizeconstraintset-sizeconstraint-fieldtomatch') } # ------------------------------------------- class WAFRegionalAction(AWSProperty): """# Action - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-action.html", "Properties": { "Type": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-action.html#cfn-wafregional-webacl-action-type", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'Type': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-webacl-action.html#cfn-wafregional-webacl-action-type') } # ------------------------------------------- class WAFRegionalFieldToMatch(AWSProperty): """# FieldToMatch - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-fieldtomatch.html", "Properties": { "Data": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-fieldtomatch.html#cfn-wafregional-sizeconstraintset-fieldtomatch-data", "PrimitiveType": "String", "Required": false, "UpdateType": "Mutable" }, "Type": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-fieldtomatch.html#cfn-wafregional-sizeconstraintset-fieldtomatch-type", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'Type': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-fieldtomatch.html#cfn-wafregional-sizeconstraintset-fieldtomatch-type'), 'Data': (basestring, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sizeconstraintset-fieldtomatch.html#cfn-wafregional-sizeconstraintset-fieldtomatch-data') } # ------------------------------------------- class WAFRegionalPredicate(AWSProperty): """# Predicate - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-rule-predicate.html", "Properties": { "DataId": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-rule-predicate.html#cfn-wafregional-rule-predicate-dataid", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" }, "Negated": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-rule-predicate.html#cfn-wafregional-rule-predicate-negated", "PrimitiveType": "Boolean", "Required": true, "UpdateType": "Mutable" }, "Type": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-rule-predicate.html#cfn-wafregional-rule-predicate-type", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'Type': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-rule-predicate.html#cfn-wafregional-rule-predicate-type'), 'DataId': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-rule-predicate.html#cfn-wafregional-rule-predicate-dataid'), 'Negated': (boolean, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-rule-predicate.html#cfn-wafregional-rule-predicate-negated') } # ------------------------------------------- class WAFRegionalFieldToMatch(AWSProperty): """# FieldToMatch - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-fieldtomatch.html", "Properties": { "Data": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-fieldtomatch.html#cfn-wafregional-sqlinjectionmatchset-fieldtomatch-data", "PrimitiveType": "String", "Required": false, "UpdateType": "Mutable" }, "Type": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-fieldtomatch.html#cfn-wafregional-sqlinjectionmatchset-fieldtomatch-type", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'Type': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-fieldtomatch.html#cfn-wafregional-sqlinjectionmatchset-fieldtomatch-type'), 'Data': (basestring, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-fieldtomatch.html#cfn-wafregional-sqlinjectionmatchset-fieldtomatch-data') } # ------------------------------------------- class WAFRegionalSqlInjectionMatchTuple(AWSProperty): """# SqlInjectionMatchTuple - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple.html", "Properties": { "FieldToMatch": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple.html#cfn-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple-fieldtomatch", "Required": true, "Type": "FieldToMatch", "UpdateType": "Mutable" }, "TextTransformation": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple.html#cfn-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple-texttransformation", "PrimitiveType": "String", "Required": true, "UpdateType": "Mutable" } } } """ props = { 'TextTransformation': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple.html#cfn-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple-texttransformation'), 'FieldToMatch': (FieldToMatch, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple.html#cfn-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuple-fieldtomatch') } # ------------------------------------------- class WAFRegionalSizeConstraintSet(AWSObject): """# AWS::WAFRegional::SizeConstraintSet - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sizeconstraintset.html", "Properties": { "Name": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sizeconstraintset.html#cfn-wafregional-sizeconstraintset-name", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" }, "SizeConstraints": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sizeconstraintset.html#cfn-wafregional-sizeconstraintset-sizeconstraints", "ItemType": "SizeConstraint", "Required": false, "Type": "List", "UpdateType": "Mutable" } } } """ resource_type = "AWS::WAFRegional::SizeConstraintSet" props = { 'SizeConstraints': ([SizeConstraint], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sizeconstraintset.html#cfn-wafregional-sizeconstraintset-sizeconstraints'), 'Name': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sizeconstraintset.html#cfn-wafregional-sizeconstraintset-name') } # ------------------------------------------- class WAFRegionalSqlInjectionMatchSet(AWSObject): """# AWS::WAFRegional::SqlInjectionMatchSet - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sqlinjectionmatchset.html", "Properties": { "Name": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sqlinjectionmatchset.html#cfn-wafregional-sqlinjectionmatchset-name", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" }, "SqlInjectionMatchTuples": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sqlinjectionmatchset.html#cfn-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuples", "ItemType": "SqlInjectionMatchTuple", "Required": false, "Type": "List", "UpdateType": "Mutable" } } } """ resource_type = "AWS::WAFRegional::SqlInjectionMatchSet" props = { 'SqlInjectionMatchTuples': ([SqlInjectionMatchTuple], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sqlinjectionmatchset.html#cfn-wafregional-sqlinjectionmatchset-sqlinjectionmatchtuples'), 'Name': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-sqlinjectionmatchset.html#cfn-wafregional-sqlinjectionmatchset-name') } # ------------------------------------------- class WAFRegionalXssMatchSet(AWSObject): """# AWS::WAFRegional::XssMatchSet - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-xssmatchset.html", "Properties": { "Name": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-xssmatchset.html#cfn-wafregional-xssmatchset-name", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" }, "XssMatchTuples": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-xssmatchset.html#cfn-wafregional-xssmatchset-xssmatchtuples", "ItemType": "XssMatchTuple", "Required": false, "Type": "List", "UpdateType": "Mutable" } } } """ resource_type = "AWS::WAFRegional::XssMatchSet" props = { 'XssMatchTuples': ([XssMatchTuple], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-xssmatchset.html#cfn-wafregional-xssmatchset-xssmatchtuples'), 'Name': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-xssmatchset.html#cfn-wafregional-xssmatchset-name') } # ------------------------------------------- class WAFRegionalByteMatchSet(AWSObject): """# AWS::WAFRegional::ByteMatchSet - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-bytematchset.html", "Properties": { "ByteMatchTuples": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-bytematchset.html#cfn-wafregional-bytematchset-bytematchtuples", "ItemType": "ByteMatchTuple", "Required": false, "Type": "List", "UpdateType": "Mutable" }, "Name": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-bytematchset.html#cfn-wafregional-bytematchset-name", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" } } } """ resource_type = "AWS::WAFRegional::ByteMatchSet" props = { 'ByteMatchTuples': ([ByteMatchTuple], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-bytematchset.html#cfn-wafregional-bytematchset-bytematchtuples'), 'Name': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-bytematchset.html#cfn-wafregional-bytematchset-name') } # ------------------------------------------- class WAFRegionalWebACLAssociation(AWSObject): """# AWS::WAFRegional::WebACLAssociation - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webaclassociation.html", "Properties": { "ResourceArn": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webaclassociation.html#cfn-wafregional-webaclassociation-resourcearn", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" }, "WebACLId": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webaclassociation.html#cfn-wafregional-webaclassociation-webaclid", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" } } } """ resource_type = "AWS::WAFRegional::WebACLAssociation" props = { 'ResourceArn': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webaclassociation.html#cfn-wafregional-webaclassociation-resourcearn'), 'WebACLId': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webaclassociation.html#cfn-wafregional-webaclassociation-webaclid') } # ------------------------------------------- class WAFRegionalWebACL(AWSObject): """# AWS::WAFRegional::WebACL - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html", "Properties": { "DefaultAction": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html#cfn-wafregional-webacl-defaultaction", "Required": true, "Type": "Action", "UpdateType": "Mutable" }, "MetricName": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html#cfn-wafregional-webacl-metricname", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" }, "Name": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html#cfn-wafregional-webacl-name", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" }, "Rules": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html#cfn-wafregional-webacl-rules", "ItemType": "Rule", "Required": false, "Type": "List", "UpdateType": "Mutable" } } } """ resource_type = "AWS::WAFRegional::WebACL" props = { 'MetricName': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html#cfn-wafregional-webacl-metricname'), 'DefaultAction': (Action, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html#cfn-wafregional-webacl-defaultaction'), 'Rules': ([Rule], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html#cfn-wafregional-webacl-rules'), 'Name': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-webacl.html#cfn-wafregional-webacl-name') } # ------------------------------------------- class WAFRegionalRule(AWSObject): """# AWS::WAFRegional::Rule - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-rule.html", "Properties": { "MetricName": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-rule.html#cfn-wafregional-rule-metricname", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" }, "Name": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-rule.html#cfn-wafregional-rule-name", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" }, "Predicates": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-rule.html#cfn-wafregional-rule-predicates", "ItemType": "Predicate", "Required": false, "Type": "List", "UpdateType": "Mutable" } } } """ resource_type = "AWS::WAFRegional::Rule" props = { 'MetricName': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-rule.html#cfn-wafregional-rule-metricname'), 'Predicates': ([Predicate], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-rule.html#cfn-wafregional-rule-predicates'), 'Name': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-rule.html#cfn-wafregional-rule-name') } # ------------------------------------------- class WAFRegionalIPSet(AWSObject): """# AWS::WAFRegional::IPSet - CloudFormationResourceSpecification version: 1.4.0 { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-ipset.html", "Properties": { "IPSetDescriptors": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-ipset.html#cfn-wafregional-ipset-ipsetdescriptors", "ItemType": "IPSetDescriptor", "Required": false, "Type": "List", "UpdateType": "Mutable" }, "Name": { "Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-ipset.html#cfn-wafregional-ipset-name", "PrimitiveType": "String", "Required": true, "UpdateType": "Immutable" } } } """ resource_type = "AWS::WAFRegional::IPSet" props = { 'IPSetDescriptors': ([IPSetDescriptor], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-ipset.html#cfn-wafregional-ipset-ipsetdescriptors'), 'Name': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-wafregional-ipset.html#cfn-wafregional-ipset-name') }

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024c542586c82802a98e3a5e5ca547ed394bd6e7

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py

Python

tests/test_ccc.py

mfe/cdl_convert

1799ac2a80ccc8a5ad147c86cfa40f4de2ac266b

[ "MIT" ]

42

2015-01-26T17:52:19.000Z

2021-07-21T08:38:30.000Z

tests/test_ccc.py

mfe/cdl_convert

1799ac2a80ccc8a5ad147c86cfa40f4de2ac266b

[ "MIT" ]

26

2015-01-29T03:23:04.000Z

2021-05-27T02:14:16.000Z

tests/test_ccc.py

mfe/cdl_convert

1799ac2a80ccc8a5ad147c86cfa40f4de2ac266b

[ "MIT" ]

17

2015-08-05T13:27:45.000Z

2022-02-19T20:52:22.000Z

#!/usr/bin/env python """ Tests the ccc related functions of cdl_convert REQUIREMENTS: mock """ #============================================================================== # IMPORTS #============================================================================== # Standard Imports from decimal import Decimal try: from unittest import mock except ImportError: import mock import os import sys import tempfile import unittest from xml.etree import ElementTree # Grab our test's path and append the cdL_convert root directory # There has to be a better method than: # 1) Getting our current directory # 2) Splitting into list # 3) Splicing out the last 3 entries (filepath, test dir, tools dir) # 4) Joining # 5) Appending to our Python path. sys.path.append('/'.join(os.path.realpath(__file__).split('/')[:-2])) import cdl_convert #============================================================================== # GLOBALS #============================================================================== # parse_ccc =================================================================== CCC_FULL = """<?xml version="1.0" encoding="UTF-8"?> <ColorCorrectionCollection xmlns="urn:ASC:CDL:v1.01"> <Description>CCC description 1</Description> <InputDescription>CCC Input Desc Text</InputDescription> <Description>CCC description 2</Description> <ColorCorrection id="014_xf_seqGrade_v01"> <Description>CC description 1</Description> <InputDescription>Input Desc Text</InputDescription> <Description>CC description 2</Description> <SOPNode> <Description>Sop description 1</Description> <Description>Sop description 2</Description> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> <Description>Sop description 3</Description> </SOPNode> <Description>CC description 3</Description> <SATNode> <Description>Sat description 1</Description> <Saturation>1.09</Saturation> <Description>Sat description 2</Description> </SATNode> <Description>CC description 4</Description> <ViewingDescription>Viewing Desc Text</ViewingDescription> <Description>CC description 5</Description> </ColorCorrection> <ColorCorrection id="f51.200"> <SopNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SopNode> <SatNode> <Saturation>1.01</Saturation> </SatNode> </ColorCorrection> <ColorCorrection id="f55.100"> <Description>Raised saturation a little!?! ag... \/Offset</Description> <Description>Raised saturation a little!?! ag... \/Offset</Description> <InputDescription>METAL VIEWER!!! \/\/</InputDescription> <ViewingDescription>WOOD VIEWER!? ////</ViewingDescription> <SopNode> <Description>Raised saturation a little!?! ag... \/Offset</Description> <Slope>137829.329 4327890.9833 3489031.003</Slope> <Offset>-3424.011 -342789423.013 -4238923.11</Offset> <Power>3271893.993 .0000998 0.0000000000000000113</Power> </SopNode> <SatNode> <Saturation>1798787.01</Saturation> </SatNode> </ColorCorrection> <ColorCorrection id="f54.112"> <ASC_SAT> <Saturation>1.01</Saturation> </ASC_SAT> <ASC_SOP> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </ASC_SOP> </ColorCorrection> <Description>CCC description 3</Description> <ViewingDescription>CCC Viewing Desc Text</ViewingDescription> <Description>CCC description 4</Description> <ColorCorrection id="burp_100.x12"> <ViewingDescription></ViewingDescription> <Description></Description> <SOPNode> <Description></Description> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> </SOPNode> <Description></Description> <InputDescription></InputDescription> <SatNode> <Saturation>1.09</Saturation> <Description></Description> </SatNode> <Description></Description> </ColorCorrection> <ColorCorrection id="burp_200.x15"> <SatNode> <Description>I am a lovely sat node</Description> <Saturation>1.01</Saturation> </SatNode> </ColorCorrection> <ColorCorrection id="burp_300.x35"> <SopNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SopNode> </ColorCorrection> </ColorCorrectionCollection> """ CCC_ODD = """<?xml version="1.0" encoding="UTF-8"?> <ColorCorrectionCollection> <Description></Description> <InputDescription></InputDescription> <Description>CCC description 1</Description> <Description></Description> <Description></Description> <Description></Description> <ColorCorrection id="014_xf_seqGrade_v01"> <SOPNode> <Description>Sop description 1</Description> <Description>Sop description 2</Description> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> <Description>Sop description 3</Description> </SOPNode> </ColorCorrection> <ColorCorrection id="f51.200"> <SopNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SopNode> </ColorCorrection> <Description>Raised1 saturation a little!?! ag... \/Offset</Description> <Description>Raised2 saturation a little!?! ag... \/Offset</Description> <ColorCorrection id="f55.100"> <SatNode> <Saturation>1798787.01</Saturation> </SatNode> </ColorCorrection> <ColorCorrection id="f54.112"> <ASC_SAT> <Saturation>1.01</Saturation> </ASC_SAT> </ColorCorrection> <ViewingDescription></ViewingDescription> <ColorCorrection id="burp_200.x15"> <SatNode> <Description>I am a lovely sat node</Description> <Saturation>1.01</Saturation> </SatNode> </ColorCorrection> </ColorCorrectionCollection> """ # write_ccc =================================================================== CCC_FULL_WRITE = """<?xml version="1.0" encoding="UTF-8"?> <ColorCorrectionCollection xmlns="urn:ASC:CDL:v1.01"> <InputDescription>CCC Input Desc Text</InputDescription> <ViewingDescription>CCC Viewing Desc Text</ViewingDescription> <Description>CCC description 1</Description> <Description>CCC description 2</Description> <Description>CCC description 3</Description> <Description>CCC description 4</Description> <ColorCorrection id="014_xf_seqGrade_v01"> <InputDescription>Input Desc Text</InputDescription> <ViewingDescription>Viewing Desc Text</ViewingDescription> <Description>CC description 1</Description> <Description>CC description 2</Description> <Description>CC description 3</Description> <Description>CC description 4</Description> <Description>CC description 5</Description> <SOPNode> <Description>Sop description 1</Description> <Description>Sop description 2</Description> <Description>Sop description 3</Description> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> </SOPNode> <SATNode> <Description>Sat description 1</Description> <Description>Sat description 2</Description> <Saturation>1.09</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="f51.200"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> <SATNode> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="f55.100"> <InputDescription>METAL VIEWER!!! \/\/</InputDescription> <ViewingDescription>WOOD VIEWER!? ////</ViewingDescription> <Description>Raised saturation a little!?! ag... \/Offset</Description> <Description>Raised saturation a little!?! ag... \/Offset</Description> <SOPNode> <Description>Raised saturation a little!?! ag... \/Offset</Description> <Slope>137829.329 4327890.9833 3489031.003</Slope> <Offset>-3424.011 -342789423.013 -4238923.11</Offset> <Power>3271893.993 0.0000998 0.0000000000000000113</Power> </SOPNode> <SATNode> <Saturation>1798787.01</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="f54.112"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> <SATNode> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="burp_100.x12"> <SOPNode> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> </SOPNode> <SATNode> <Saturation>1.09</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="burp_200.x15"> <SATNode> <Description>I am a lovely sat node</Description> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="burp_300.x35"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> </ColorCorrection> </ColorCorrectionCollection> """ CCC_FULL_WRITE_CDL = """<?xml version="1.0" encoding="UTF-8"?> <ColorDecisionList xmlns="urn:ASC:CDL:v1.01"> <InputDescription>CCC Input Desc Text</InputDescription> <ViewingDescription>CCC Viewing Desc Text</ViewingDescription> <Description>CCC description 1</Description> <Description>CCC description 2</Description> <Description>CCC description 3</Description> <Description>CCC description 4</Description> <ColorDecision> <ColorCorrection id="014_xf_seqGrade_v01"> <InputDescription>Input Desc Text</InputDescription> <ViewingDescription>Viewing Desc Text</ViewingDescription> <Description>CC description 1</Description> <Description>CC description 2</Description> <Description>CC description 3</Description> <Description>CC description 4</Description> <Description>CC description 5</Description> <SOPNode> <Description>Sop description 1</Description> <Description>Sop description 2</Description> <Description>Sop description 3</Description> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> </SOPNode> <SATNode> <Description>Sat description 1</Description> <Description>Sat description 2</Description> <Saturation>1.09</Saturation> </SATNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="f51.200"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> <SATNode> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="f55.100"> <InputDescription>METAL VIEWER!!! \/\/</InputDescription> <ViewingDescription>WOOD VIEWER!? ////</ViewingDescription> <Description>Raised saturation a little!?! ag... \/Offset</Description> <Description>Raised saturation a little!?! ag... \/Offset</Description> <SOPNode> <Description>Raised saturation a little!?! ag... \/Offset</Description> <Slope>137829.329 4327890.9833 3489031.003</Slope> <Offset>-3424.011 -342789423.013 -4238923.11</Offset> <Power>3271893.993 0.0000998 0.0000000000000000113</Power> </SOPNode> <SATNode> <Saturation>1798787.01</Saturation> </SATNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="f54.112"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> <SATNode> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="burp_100.x12"> <SOPNode> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> </SOPNode> <SATNode> <Saturation>1.09</Saturation> </SATNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="burp_200.x15"> <SATNode> <Description>I am a lovely sat node</Description> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="burp_300.x35"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> </ColorCorrection> </ColorDecision> </ColorDecisionList> """ CCC_ODD_WRITE = """<?xml version="1.0" encoding="UTF-8"?> <ColorCorrectionCollection xmlns="urn:ASC:CDL:v1.01"> <Description>CCC description 1</Description> <Description>Raised1 saturation a little!?! ag... \/Offset</Description> <Description>Raised2 saturation a little!?! ag... \/Offset</Description> <ColorCorrection id="014_xf_seqGrade_v01"> <SOPNode> <Description>Sop description 1</Description> <Description>Sop description 2</Description> <Description>Sop description 3</Description> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> </SOPNode> </ColorCorrection> <ColorCorrection id="f51.200"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> </ColorCorrection> <ColorCorrection id="f55.100"> <SATNode> <Saturation>1798787.01</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="f54.112"> <SATNode> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="burp_200.x15"> <SATNode> <Description>I am a lovely sat node</Description> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> </ColorCorrectionCollection> """ CCC_ODD_WRITE_CDL = """<?xml version="1.0" encoding="UTF-8"?> <ColorDecisionList xmlns="urn:ASC:CDL:v1.01"> <Description>CCC description 1</Description> <Description>Raised1 saturation a little!?! ag... \/Offset</Description> <Description>Raised2 saturation a little!?! ag... \/Offset</Description> <ColorDecision> <ColorCorrection id="014_xf_seqGrade_v01"> <SOPNode> <Description>Sop description 1</Description> <Description>Sop description 2</Description> <Description>Sop description 3</Description> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> </SOPNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="f51.200"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="f55.100"> <SATNode> <Saturation>1798787.01</Saturation> </SATNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="f54.112"> <SATNode> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> </ColorDecision> <ColorDecision> <ColorCorrection id="burp_200.x15"> <SATNode> <Description>I am a lovely sat node</Description> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> </ColorDecision> </ColorDecisionList> """ CCC_BAD_TAG = """<?xml version="1.0" encoding="UTF-8"?> <ColorCorrectionBollection xmlns="urn:ASC:CDL:v1.01"> <Description>CCC description 1</Description> <Description>Raised1 saturation a little!?! ag... \/Offset</Description> <Description>Raised2 saturation a little!?! ag... \/Offset</Description> <ColorCorrection id="014_xf_seqGrade_v01"> <SOPNode> <Description>Sop description 1</Description> <Description>Sop description 2</Description> <Description>Sop description 3</Description> <Slope>1.014 1.0104 0.62</Slope> <Offset>-0.00315 -0.00124 0.3103</Offset> <Power>1.0 0.9983 1.0</Power> </SOPNode> </ColorCorrection> <ColorCorrection id="f51.200"> <SOPNode> <Slope>0.2331 0.678669 1.0758</Slope> <Offset>0.031 0.128 -0.096</Offset> <Power>1.8 0.97 0.961</Power> </SOPNode> </ColorCorrection> <ColorCorrection id="f55.100"> <SATNode> <Saturation>1798787.01</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="f54.112"> <SATNode> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> <ColorCorrection id="burp_200.x15"> <SATNode> <Description>I am a lovely sat node</Description> <Saturation>1.01</Saturation> </SATNode> </ColorCorrection> </ColorCorrectionBollection> """ # misc ======================================================================== UPPER = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' LOWER = 'abcdefghijklmnopqrstuvwxyz' if sys.version_info[0] >= 3: enc = lambda x: bytes(x, 'UTF-8') else: enc = lambda x: x if sys.version_info[0] >= 3: builtins = 'builtins' else: builtins = '__builtin__' #============================================================================== # TEST CLASSES #============================================================================== class TestParseCCCFull(unittest.TestCase): """Tests a full CCC parse""" #========================================================================== # SETUP & TEARDOWN #========================================================================== def setUp(self): self.desc = [ 'CCC description 1', 'CCC description 2', 'CCC description 3', 'CCC description 4' ] self.input_desc = 'CCC Input Desc Text' self.viewing_desc = 'CCC Viewing Desc Text' self.color_correction_ids = [ '014_xf_seqGrade_v01', 'f51.200', 'f55.100', 'f54.112', 'burp_100.x12', 'burp_200.x15', 'burp_300.x35' ] # Build our ccc with tempfile.NamedTemporaryFile(mode='wb', delete=False) as f: f.write(enc(CCC_FULL)) self.filename = f.name self.node = cdl_convert.parse_ccc(self.filename) #========================================================================== def tearDown(self): # The system should clean these up automatically, # but we'll be neat. os.remove(self.filename) # We need to clear the ColorCorrection member dictionary so we don't # have to worry about non-unique ids. cdl_convert.reset_all() #========================================================================== # TESTS #========================================================================== def test_file_in(self): """Tests that the input_file has been set to the file in value""" self.assertEqual( self.filename, self.node.file_in ) #========================================================================== def test_type(self): """Makes sure type is still set to ccc""" self.assertEqual( 'ccc', self.node.type ) #========================================================================== def test_descs(self): """Tests that the desc fields have been set correctly""" self.assertEqual( self.desc, self.node.desc ) #========================================================================== def test_viewing_desc(self): """Tests that the viewing desc has been set correctly""" self.assertEqual( self.viewing_desc, self.node.viewing_desc ) #========================================================================== def test_input_desc(self): """Tests that the input desc has been set correctly""" self.assertEqual( self.input_desc, self.node.input_desc ) #========================================================================== def test_parse_results(self): """Tests that the parser picked up all the cc's""" id_list = [i.id for i in self.node.color_corrections] self.assertEqual( self.color_correction_ids, id_list ) class TestParseCCCOdd(TestParseCCCFull): """Tests an odd CCC parse""" #========================================================================== # SETUP & TEARDOWN #========================================================================== def setUp(self): self.desc = [ 'CCC description 1', 'Raised1 saturation a little!?! ag... \/Offset', 'Raised2 saturation a little!?! ag... \/Offset', ] self.input_desc = None self.viewing_desc = None self.color_correction_ids = [ '014_xf_seqGrade_v01', 'f51.200', 'f55.100', 'f54.112', 'burp_200.x15', ] # Build our ccc with tempfile.NamedTemporaryFile(mode='wb', delete=False) as f: f.write(enc(CCC_ODD)) self.filename = f.name self.node = cdl_convert.parse_ccc(self.filename) class TestParseCCCExceptions(unittest.TestCase): """Tests that we run into the correct exceptions with bad XMLs""" #========================================================================== # SETUP & TEARDOWN #========================================================================== def setUp(self): self.filename = None def tearDown(self): if self.filename: os.remove(self.filename) cdl_convert.reset_all() #========================================================================== # TESTS #========================================================================== def testBadTag(self): """Tests that a bad root tag raises a ValueError""" # Build our ccc with tempfile.NamedTemporaryFile(mode='wb', delete=False) as f: f.write(enc(CCC_BAD_TAG)) self.filename = f.name self.assertRaises( ValueError, cdl_convert.parse_ccc, self.filename, ) #========================================================================== def testEmptyCCC(self): """Tests that an empty CCC file raises a ValueError""" emptyCCC = ('<?xml version="1.0" encoding="UTF-8"?>\n' '<ColorCorrectionCollection xmlns="urn:ASC:CDL:v1.01">\n' '</ColorCorrectionCollection>') # Build our ccc with tempfile.NamedTemporaryFile(mode='wb', delete=False) as f: f.write(enc(emptyCCC)) self.filename = f.name self.assertRaises( ValueError, cdl_convert.parse_ccc, self.filename, ) class TestWriteCCCFull(unittest.TestCase): """Tests a full write of the CCC file This is an integration style test. If parse_ccc stops working, this stops working. """ #========================================================================== # SETUP & TEARDOWN #========================================================================== def setUp(self): # Build our ccc with tempfile.NamedTemporaryFile(mode='wb', delete=False) as f: f.write(enc(CCC_FULL)) self.filename = f.name self.ccc = cdl_convert.parse_ccc(self.filename) self.target_xml_root = enc(CCC_FULL_WRITE) self.target_xml = enc('\n'.join(CCC_FULL_WRITE.split('\n')[1:])) #========================================================================== def tearDown(self): os.remove(self.filename) cdl_convert.reset_all() #========================================================================== # TESTS #========================================================================== def test_root_xml(self): """Tests that root_xml returns the full XML as expected""" self.assertEqual( self.target_xml_root, self.ccc.xml_root ) #========================================================================== def test_base_xml(self): """Tests that the xml atrib returns the XML minus root as expected""" self.assertEqual( self.target_xml, self.ccc.xml ) #========================================================================== def test_element(self): """Tests that the element returned is an etree type""" self.assertEqual( 'ColorCorrectionCollection', self.ccc.element.tag ) #========================================================================== def test_write(self): """Tests writing the ccc itself""" mockOpen = mock.mock_open() self.ccc._file_out = 'bobs_big_file.ccc' with mock.patch(builtins + '.open', mockOpen, create=True): cdl_convert.write_ccc(self.ccc) mockOpen.assert_called_once_with('bobs_big_file.ccc', 'wb') mockOpen().write.assert_called_once_with(self.target_xml_root) class TestWriteCCCFullAsCDL(TestWriteCCCFull): """Tests a full write of the CCC file as a CDL This is an integration style test. If parse_ccc stops working, this stops working. """ #========================================================================== # SETUP & TEARDOWN #========================================================================== def setUp(self): # Build our ccc with tempfile.NamedTemporaryFile(mode='wb', delete=False) as f: f.write(enc(CCC_FULL)) self.filename = f.name self.ccc = cdl_convert.parse_ccc(self.filename) self.ccc.set_to_cdl() self.target_xml_root = enc(CCC_FULL_WRITE_CDL) self.target_xml = enc('\n'.join(CCC_FULL_WRITE_CDL.split('\n')[1:])) #========================================================================== def test_element(self): """Tests that the element returned is an etree type""" self.assertEqual( 'ColorDecisionList', self.ccc.element.tag ) #========================================================================== def test_write(self): """Tests writing the ccc itself""" mockOpen = mock.mock_open() self.ccc._file_out = 'bobs_big_file.cdl' with mock.patch(builtins + '.open', mockOpen, create=True): cdl_convert.write_cdl(self.ccc) mockOpen.assert_called_once_with('bobs_big_file.cdl', 'wb') mockOpen().write.assert_called_once_with(self.target_xml_root) class TestWriteCCCOdd(TestWriteCCCFull): """Tests an odd write of the CCC file This is an integration style test. If parse_ccc stops working, this stops working. """ #========================================================================== # SETUP & TEARDOWN #========================================================================== def setUp(self): cdl_convert.reset_all() # Build our ccc with tempfile.NamedTemporaryFile(mode='wb', delete=False) as f: f.write(enc(CCC_ODD)) self.filename = f.name self.ccc = cdl_convert.parse_ccc(self.filename) self.target_xml_root = enc(CCC_ODD_WRITE) self.target_xml = enc('\n'.join(CCC_ODD_WRITE.split('\n')[1:])) class TestWriteCCCOddAsCDL(TestWriteCCCFullAsCDL): """Tests a full write of the CCC file as a CDL This is an integration style test. If parse_ccc stops working, this stops working. """ #========================================================================== # SETUP & TEARDOWN #========================================================================== def setUp(self): # Build our ccc with tempfile.NamedTemporaryFile(mode='wb', delete=False) as f: f.write(enc(CCC_ODD)) self.filename = f.name self.ccc = cdl_convert.parse_ccc(self.filename) self.ccc.set_to_cdl() self.target_xml_root = enc(CCC_ODD_WRITE_CDL) self.target_xml = enc('\n'.join(CCC_ODD_WRITE_CDL.split('\n')[1:])) #============================================================================== # RUNNER #============================================================================== if __name__ == '__main__': unittest.main()

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02694fd1202c980b2d7a0d74d92e632c119fc0b2

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Python

pscheduler-tool-iperf3/iperf3/iperf3_parser.py

igarny/pscheduler

0ab6e68bb3adb808e1116bab0eb7438bf4c31e2c

[ "Apache-2.0" ]

null

pscheduler-tool-iperf3/iperf3/iperf3_parser.py

igarny/pscheduler

0ab6e68bb3adb808e1116bab0eb7438bf4c31e2c

[ "Apache-2.0" ]

null

pscheduler-tool-iperf3/iperf3/iperf3_parser.py

igarny/pscheduler

0ab6e68bb3adb808e1116bab0eb7438bf4c31e2c

[ "Apache-2.0" ]

null

import re import pscheduler import pprint import json logger = pscheduler.Log(quiet=True) # A whole bunch of pattern matching against the output of the "iperf3" tool # client output. Builds up an object of interesting bits from it. def parse_output(lines): results = {} results['succeeded'] = True try: content = json.loads("".join(lines)) except Exception as e: results['succeeded'] = False results['error'] = "Unable to parse iperf3 output as JSON: %s" % e return results intervals = [] if content.has_key('intervals'): intervals = content['intervals'] else: results['succeeded'] = False results['error'] = "iperf3 output is missing required field 'intervals'" return results final_streams = [] # Go through the JSON and convert to what we're expecting in throughput tests # This is mostly a renaming since it's so similar for interval in intervals: #these don't appear to be required by json schema, so ignoring if missing streams = interval.get('streams', []) summary = interval.get('sum', {}) renamed_streams = [] for stream in streams: new_stream = rename_json(stream) renamed_streams.append(new_stream) renamed_summary = rename_json(summary) final_streams.append({ "streams": renamed_streams, "summary": renamed_summary }) sum_end = {} if content.has_key('end'): sum_end = content['end'] else: results['succeeded'] = False results['error'] = "iperf3 output is missing required field 'end'" return results # the "summary" keys are different for UDP/TCP here if sum_end.has_key("sum_sent"): summary = sum_end["sum_sent"] elif sum_end.has_key("sum"): summary = sum_end['sum'] else: results['succeeded'] = False results['error'] = "iperf3 output has neither 'sum_sent' nor 'sum' field, and one of them is required" return results renamed_summary = rename_json(summary) # kind of like above, the streams summary is in a different key # json schema does not require, so ignore if not provided sum_streams = sum_end.get('streams', []) renamed_sum_streams = [] for sum_stream in sum_streams: if sum_stream.has_key("udp"): renamed_sum_streams.append(rename_json(sum_stream['udp'])) elif sum_stream.has_key("sender"): renamed_sum_streams.append(rename_json(sum_stream['sender'])) results["intervals"] = final_streams results["summary"] = {"streams": renamed_sum_streams, "summary": renamed_summary} return results def rename_json(obj): new_obj = {} lookup = { "socket": "stream-id", "start": "start", "end": "end", "bytes": "throughput-bytes", "bits_per_second": "throughput-bits", "omitted": "omitted", "jitter_ms": "jitter", # only for UDP "packets": "sent", "lost_packets": "lost", # only for TCP "retransmits": "retransmits", "snd_cwnd": "tcp-window-size", "rtt": "rtt", "mean_rtt": "rtt" } for k,v in obj.iteritems(): if lookup.has_key(k): new_obj[lookup[k]] = v return new_obj if __name__ == "__main__": # Test "regular" output test_output = """ { "start": { "connected": [{ "socket": 4, "local_host": "10.0.2.15", "local_port": 33600, "remote_host": "10.0.2.4", "remote_port": 5201 }], "version": "iperf 3.1.3", "system_info": "Linux ps-test1 2.6.32-642.3.1.el6.x86_64 #1 SMP Tue Jul 12 18:30:56 UTC 2016 x86_64", "timestamp": { "time": "Tue, 16 Aug 2016 03:39:47 GMT", "timesecs": 1471318787 }, "connecting_to": { "host": "10.0.2.4", "port": 5201 }, "cookie": "ps-test1.1471318787.639126.54345cb13", "tcp_mss_default": 1448, "test_start": { "protocol": "TCP", "num_streams": 1, "blksize": 131072, "omit": 0, "duration": 10, "bytes": 0, "blocks": 0, "reverse": 0 } }, "intervals": [{ "streams": [{ "socket": 4, "start": 0, "end": 1.000375, "seconds": 1.000375, "bytes": 1982312, "bits_per_second": 15852550.779440, "retransmits": 4, "snd_cwnd": 53576, "rtt": 7375, "omitted": false }], "sum": { "start": 0, "end": 1.000375, "seconds": 1.000375, "bytes": 1982312, "bits_per_second": 15852550.779440, "retransmits": 4, "omitted": false } }, { "streams": [{ "socket": 4, "start": 1.000375, "end": 2.004007, "seconds": 1.003632, "bytes": 301184, "bits_per_second": 2400752.302863, "retransmits": 2, "snd_cwnd": 53576, "rtt": 67000, "omitted": false }], "sum": { "start": 1.000375, "end": 2.004007, "seconds": 1.003632, "bytes": 301184, "bits_per_second": 2400752.302863, "retransmits": 2, "omitted": false } }, { "streams": [{ "socket": 4, "start": 2.004007, "end": 3.002219, "seconds": 0.998212, "bytes": 860864, "bits_per_second": 6899248.818251, "retransmits": 1, "snd_cwnd": 72400, "rtt": 3375, "omitted": false }], "sum": { "start": 2.004007, "end": 3.002219, "seconds": 0.998212, "bytes": 860864, "bits_per_second": 6899248.818251, "retransmits": 1, "omitted": false } }, { "streams": [{ "socket": 4, "start": 3.002219, "end": 4.003231, "seconds": 1.001012, "bytes": 2033744, "bits_per_second": 16253502.044018, "retransmits": 3, "snd_cwnd": 99912, "rtt": 10500, "omitted": false }], "sum": { "start": 3.002219, "end": 4.003231, "seconds": 1.001012, "bytes": 2033744, "bits_per_second": 16253502.044018, "retransmits": 3, "omitted": false } }, { "streams": [{ "socket": 4, "start": 4.003231, "end": 5.000839, "seconds": 0.997608, "bytes": 2805528, "bits_per_second": 22498040.518909, "retransmits": 3, "snd_cwnd": 136112, "rtt": 3750, "omitted": false }], "sum": { "start": 4.003231, "end": 5.000839, "seconds": 0.997608, "bytes": 2805528, "bits_per_second": 22498040.518909, "retransmits": 3, "omitted": false } }, { "streams": [{ "socket": 4, "start": 5.000839, "end": 6.002020, "seconds": 1.001181, "bytes": 23605296, "bits_per_second": 188619584.572292, "retransmits": 48, "snd_cwnd": 36200, "rtt": 1875, "omitted": false }], "sum": { "start": 5.000839, "end": 6.002020, "seconds": 1.001181, "bytes": 23605296, "bits_per_second": 188619584.572292, "retransmits": 48, "omitted": false } }, { "streams": [{ "socket": 4, "start": 6.002020, "end": 7.000188, "seconds": 0.998168, "bytes": 52243840, "bits_per_second": 418717814.537474, "retransmits": 48, "snd_cwnd": 194032, "rtt": 1875, "omitted": false }], "sum": { "start": 6.002020, "end": 7.000188, "seconds": 0.998168, "bytes": 52243840, "bits_per_second": 418717814.537474, "retransmits": 48, "omitted": false } }, { "streams": [{ "socket": 4, "start": 7.000188, "end": 8.000270, "seconds": 1.000082, "bytes": 179971920, "bits_per_second": 1.439657e+09, "retransmits": 1, "snd_cwnd": 231680, "rtt": 1875, "omitted": false }], "sum": { "start": 7.000188, "end": 8.000270, "seconds": 1.000082, "bytes": 179971920, "bits_per_second": 1.439657e+09, "retransmits": 1, "omitted": false } }, { "streams": [{ "socket": 4, "start": 8.000270, "end": 9.000164, "seconds": 0.999894, "bytes": 213855120, "bits_per_second": 1.711022e+09, "retransmits": 45, "snd_cwnd": 204168, "rtt": 1875, "omitted": false }], "sum": { "start": 8.000270, "end": 9.000164, "seconds": 0.999894, "bytes": 213855120, "bits_per_second": 1.711022e+09, "retransmits": 45, "omitted": false } }, { "streams": [{ "socket": 4, "start": 9.000164, "end": 10.001024, "seconds": 1.000860, "bytes": 8983392, "bits_per_second": 71805385.105436, "retransmits": 4, "snd_cwnd": 60816, "rtt": 2250, "omitted": false }], "sum": { "start": 9.000164, "end": 10.001024, "seconds": 1.000860, "bytes": 8983392, "bits_per_second": 71805385.105436, "retransmits": 4, "omitted": false } }], "end": { "streams": [{ "sender": { "socket": 4, "start": 0, "end": 10.001024, "seconds": 10.001024, "bytes": 486643200, "bits_per_second": 389274697.967401, "retransmits": 159, "max_snd_cwnd": 231680, "max_rtt": 67000, "min_rtt": 1875, "mean_rtt": 10175 }, "receiver": { "socket": 4, "start": 0, "end": 10.001024, "seconds": 10.001024, "bytes": 485969880, "bits_per_second": 388736097.120548 } }], "sum_sent": { "start": 0, "end": 10.001024, "seconds": 10.001024, "bytes": 486643200, "bits_per_second": 389274697.967401, "retransmits": 159 }, "sum_received": { "start": 0, "end": 10.001024, "seconds": 10.001024, "bytes": 485969880, "bits_per_second": 388736097.120548 }, "cpu_utilization_percent": { "host_total": 2.181510, "host_user": 0.148710, "host_system": 2.101865, "remote_total": 4.763802, "remote_user": 0.015363, "remote_system": 4.763079 } } } """ result = parse_output(test_output.split("\n")) pprint.PrettyPrinter(indent=4).pprint(result) test_output = """ { "start": { "connected": [{ "socket": 4, "local_host": "10.0.2.15", "local_port": 49036, "remote_host": "10.0.2.4", "remote_port": 5201 }], "version": "iperf 3.1.3", "system_info": "Linux ps-test1 2.6.32-642.3.1.el6.x86_64 #1 SMP Tue Jul 12 18:30:56 UTC 2016 x86_64", "timestamp": { "time": "Tue, 16 Aug 2016 04:48:35 GMT", "timesecs": 1471322915 }, "connecting_to": { "host": "10.0.2.4", "port": 5201 }, "cookie": "ps-test1.1471322915.508871.24c661250", "test_start": { "protocol": "UDP", "num_streams": 1, "blksize": 8192, "omit": 0, "duration": 10, "bytes": 0, "blocks": 0, "reverse": 0 } }, "intervals": [{ "streams": [{ "socket": 4, "start": 0, "end": 1.001342, "seconds": 1.001342, "bytes": 131072, "bits_per_second": 1047170.885411, "packets": 16, "omitted": false }], "sum": { "start": 0, "end": 1.001342, "seconds": 1.001342, "bytes": 131072, "bits_per_second": 1047170.885411, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 1.001342, "end": 2.001610, "seconds": 1.000268, "bytes": 131072, "bits_per_second": 1048295.075283, "packets": 16, "omitted": false }], "sum": { "start": 1.001342, "end": 2.001610, "seconds": 1.000268, "bytes": 131072, "bits_per_second": 1048295.075283, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 2.001610, "end": 3.001298, "seconds": 0.999688, "bytes": 131072, "bits_per_second": 1048903.102007, "packets": 16, "omitted": false }], "sum": { "start": 2.001610, "end": 3.001298, "seconds": 0.999688, "bytes": 131072, "bits_per_second": 1048903.102007, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 3.001298, "end": 4.001750, "seconds": 1.000452, "bytes": 131072, "bits_per_second": 1048102.214171, "packets": 16, "omitted": false }], "sum": { "start": 3.001298, "end": 4.001750, "seconds": 1.000452, "bytes": 131072, "bits_per_second": 1048102.214171, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 4.001750, "end": 5.001297, "seconds": 0.999547, "bytes": 131072, "bits_per_second": 1049051.215270, "packets": 16, "omitted": false }], "sum": { "start": 4.001750, "end": 5.001297, "seconds": 0.999547, "bytes": 131072, "bits_per_second": 1049051.215270, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 5.001297, "end": 6.000906, "seconds": 0.999609, "bytes": 131072, "bits_per_second": 1048986.160375, "packets": 16, "omitted": false }], "sum": { "start": 5.001297, "end": 6.000906, "seconds": 0.999609, "bytes": 131072, "bits_per_second": 1048986.160375, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 6.000906, "end": 7.001737, "seconds": 1.000831, "bytes": 131072, "bits_per_second": 1047705.473311, "packets": 16, "omitted": false }], "sum": { "start": 6.000906, "end": 7.001737, "seconds": 1.000831, "bytes": 131072, "bits_per_second": 1047705.473311, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 7.001737, "end": 8.001043, "seconds": 0.999306, "bytes": 131072, "bits_per_second": 1049304.255436, "packets": 16, "omitted": false }], "sum": { "start": 7.001737, "end": 8.001043, "seconds": 0.999306, "bytes": 131072, "bits_per_second": 1049304.255436, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 8.001043, "end": 9.001251, "seconds": 1.000208, "bytes": 131072, "bits_per_second": 1048357.795417, "packets": 16, "omitted": false }], "sum": { "start": 8.001043, "end": 9.001251, "seconds": 1.000208, "bytes": 131072, "bits_per_second": 1048357.795417, "packets": 16, "omitted": false } }, { "streams": [{ "socket": 4, "start": 9.001251, "end": 10.000900, "seconds": 0.999649, "bytes": 131072, "bits_per_second": 1048944.129196, "packets": 16, "omitted": false }], "sum": { "start": 9.001251, "end": 10.000900, "seconds": 0.999649, "bytes": 131072, "bits_per_second": 1048944.129196, "packets": 16, "omitted": false } }], "end": { "streams": [{ "udp": { "socket": 4, "start": 0, "end": 10.000900, "seconds": 10.000900, "bytes": 1310720, "bits_per_second": 1048481.633493, "jitter_ms": 2735.461000, "lost_packets": 0, "packets": 159, "lost_percent": 0, "out_of_order": 0 } }], "sum": { "start": 0, "end": 10.000900, "seconds": 10.000900, "bytes": 1310720, "bits_per_second": 1048481.633493, "jitter_ms": 2735.461000, "lost_packets": 0, "packets": 159, "lost_percent": 0 }, "cpu_utilization_percent": { "host_total": 0.892589, "host_user": 0.019825, "host_system": 0.971782, "remote_total": 0.135247, "remote_user": 0, "remote_system": 0.135226 } } } """ result = parse_output(test_output.split("\n")) pprint.PrettyPrinter(indent=4).pprint(result) test_output = """ { "start": { "connected": [{ "socket": 4, "local_host": "150.254.208.65", "local_port": 35026, "remote_host": "140.182.44.177", "remote_port": 5201 }], "version": "iperf 3.1.6", "system_info": "Linux ps-4-0 4.4.0-59-generic #80~14.04.1-Ubuntu SMP Fri Jan 6 18:02:02 UTC 2017 x86_64", "timestamp": { "time": "Mon, 13 Feb 2017 19:14:16 GMT", "timesecs": 1487013256 }, "connecting_to": { "host": "140.182.44.177", "port": 5201 }, "cookie": "ps-4-0.1487013255.986166.651993251aa", "tcp_mss_default": 1448, "test_start": { "protocol": "TCP", "num_streams": 1, "blksize": 131072, "omit": 0, "duration": 20, "bytes": 0, "blocks": 0, "reverse": 0 } }, "intervals": [{ "streams": [{ "socket": 4, "start": 0, "end": 1.000095, "seconds": 1.000095, "bytes": 2255984, "bits_per_second": 18046155.287058, "retransmits": 0, "snd_cwnd": 350416, "rtt": 134320, "omitted": false }], "sum": { "start": 0, "end": 1.000095, "seconds": 1.000095, "bytes": 2255984, "bits_per_second": 18046155.287058, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 1.000095, "end": 2.000278, "seconds": 1.000183, "bytes": 3598840, "bits_per_second": 28785456.088557, "retransmits": 137, "snd_cwnd": 209960, "rtt": 134534, "omitted": false }], "sum": { "start": 1.000095, "end": 2.000278, "seconds": 1.000183, "bytes": 3598840, "bits_per_second": 28785456.088557, "retransmits": 137, "omitted": false } }, { "streams": [{ "socket": 4, "start": 2.000278, "end": 3.000251, "seconds": 0.999973, "bytes": 1310720, "bits_per_second": 10486042.507611, "retransmits": 0, "snd_cwnd": 221544, "rtt": 134808, "omitted": false }], "sum": { "start": 2.000278, "end": 3.000251, "seconds": 0.999973, "bytes": 1310720, "bits_per_second": 10486042.507611, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 3.000251, "end": 4.003264, "seconds": 1.003013, "bytes": 2621440, "bits_per_second": 20908519.827961, "retransmits": 0, "snd_cwnd": 318560, "rtt": 140105, "omitted": false }], "sum": { "start": 3.000251, "end": 4.003264, "seconds": 1.003013, "bytes": 2621440, "bits_per_second": 20908519.827961, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 4.003264, "end": 5.000230, "seconds": 0.996966, "bytes": 2621440, "bits_per_second": 21035343.648278, "retransmits": 0, "snd_cwnd": 543000, "rtt": 134169, "omitted": false }], "sum": { "start": 4.003264, "end": 5.000230, "seconds": 0.996966, "bytes": 2621440, "bits_per_second": 21035343.648278, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 5.000230, "end": 6.000112, "seconds": 0.999882, "bytes": 5242880, "bits_per_second": 41947990.584254, "retransmits": 0, "snd_cwnd": 834048, "rtt": 137125, "omitted": false }], "sum": { "start": 5.000230, "end": 6.000112, "seconds": 0.999882, "bytes": 5242880, "bits_per_second": 41947990.584254, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 6.000112, "end": 7.000081, "seconds": 0.999969, "bytes": 9175040, "bits_per_second": 73402595.070514, "retransmits": 0, "snd_cwnd": 1274240, "rtt": 134496, "omitted": false }], "sum": { "start": 6.000112, "end": 7.000081, "seconds": 0.999969, "bytes": 9175040, "bits_per_second": 73402595.070514, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 7.000081, "end": 8.000090, "seconds": 1.000009, "bytes": 13107200, "bits_per_second": 104856650.008607, "retransmits": 0, "snd_cwnd": 1918600, "rtt": 134377, "omitted": false }], "sum": { "start": 7.000081, "end": 8.000090, "seconds": 1.000009, "bytes": 13107200, "bits_per_second": 104856650.008607, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 8.000090, "end": 9.000100, "seconds": 1.000010, "bytes": 19660800, "bits_per_second": 157284825.015771, "retransmits": 0, "snd_cwnd": 2735272, "rtt": 134310, "omitted": false }], "sum": { "start": 8.000090, "end": 9.000100, "seconds": 1.000010, "bytes": 19660800, "bits_per_second": 157284825.015771, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 9.000100, "end": 10.000086, "seconds": 0.999986, "bytes": 27525120, "bits_per_second": 220204057.543572, "retransmits": 105, "snd_cwnd": 3095824, "rtt": 137908, "omitted": false }], "sum": { "start": 9.000100, "end": 10.000086, "seconds": 0.999986, "bytes": 27525120, "bits_per_second": 220204057.543572, "retransmits": 105, "omitted": false } }, { "streams": [{ "socket": 4, "start": 10.000086, "end": 11.000096, "seconds": 1.000010, "bytes": 14417920, "bits_per_second": 115342205.011566, "retransmits": 285, "snd_cwnd": 1849096, "rtt": 134890, "omitted": false }], "sum": { "start": 10.000086, "end": 11.000096, "seconds": 1.000010, "bytes": 14417920, "bits_per_second": 115342205.011566, "retransmits": 285, "omitted": false } }, { "streams": [{ "socket": 4, "start": 11.000096, "end": 12.000080, "seconds": 0.999984, "bytes": 14417920, "bits_per_second": 115345202.529433, "retransmits": 0, "snd_cwnd": 1901224, "rtt": 134602, "omitted": false }], "sum": { "start": 11.000096, "end": 12.000080, "seconds": 0.999984, "bytes": 14417920, "bits_per_second": 115345202.529433, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 12.000080, "end": 13.000086, "seconds": 1.000006, "bytes": 14417920, "bits_per_second": 115342672.504098, "retransmits": 0, "snd_cwnd": 2106840, "rtt": 137683, "omitted": false }], "sum": { "start": 12.000080, "end": 13.000086, "seconds": 1.000006, "bytes": 14417920, "bits_per_second": 115342672.504098, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 13.000086, "end": 14.000088, "seconds": 1.000002, "bytes": 15728640, "bits_per_second": 125828880.000458, "retransmits": 0, "snd_cwnd": 2457256, "rtt": 134995, "omitted": false }], "sum": { "start": 13.000086, "end": 14.000088, "seconds": 1.000002, "bytes": 15728640, "bits_per_second": 125828880.000458, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 14.000088, "end": 15.000085, "seconds": 0.999997, "bytes": 19660800, "bits_per_second": 157286850.001287, "retransmits": 0, "snd_cwnd": 2930752, "rtt": 134586, "omitted": false }], "sum": { "start": 14.000088, "end": 15.000085, "seconds": 0.999997, "bytes": 19660800, "bits_per_second": 157286850.001287, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 15.000085, "end": 16.000087, "seconds": 1.000002, "bytes": 19660800, "bits_per_second": 157286100.000572, "retransmits": 102, "snd_cwnd": 1637688, "rtt": 134678, "omitted": false }], "sum": { "start": 15.000085, "end": 16.000087, "seconds": 1.000002, "bytes": 19660800, "bits_per_second": 157286100.000572, "retransmits": 102, "omitted": false } }, { "streams": [{ "socket": 4, "start": 16.000087, "end": 17.000085, "seconds": 0.999998, "bytes": 11796480, "bits_per_second": 94372020.000343, "retransmits": 0, "snd_cwnd": 1647824, "rtt": 134401, "omitted": false }], "sum": { "start": 16.000087, "end": 17.000085, "seconds": 0.999998, "bytes": 11796480, "bits_per_second": 94372020.000343, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 17.000085, "end": 18.000109, "seconds": 1.000024, "bytes": 11796480, "bits_per_second": 94369567.554721, "retransmits": 0, "snd_cwnd": 1765112, "rtt": 134668, "omitted": false }], "sum": { "start": 17.000085, "end": 18.000109, "seconds": 1.000024, "bytes": 11796480, "bits_per_second": 94369567.554721, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 18.000109, "end": 19.000080, "seconds": 0.999971, "bytes": 14417920, "bits_per_second": 115346715.097590, "retransmits": 0, "snd_cwnd": 2031544, "rtt": 135142, "omitted": false }], "sum": { "start": 18.000109, "end": 19.000080, "seconds": 0.999971, "bytes": 14417920, "bits_per_second": 115346715.097590, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 19.000080, "end": 20.000215, "seconds": 1.000135, "bytes": 11796480, "bits_per_second": 94359106.718292, "retransmits": 57, "snd_cwnd": 1122200, "rtt": 135457, "omitted": false }], "sum": { "start": 19.000080, "end": 20.000215, "seconds": 1.000135, "bytes": 11796480, "bits_per_second": 94359106.718292, "retransmits": 57, "omitted": false } }], "end": { "streams": [{ "sender": { "socket": 4, "start": 0, "end": 20.000215, "seconds": 20.000215, "bytes": 235230824, "bits_per_second": 94091317.866364, "retransmits": 686, "max_snd_cwnd": 3095824, "max_rtt": 140105, "min_rtt": 134169, "mean_rtt": 135362 }, "receiver": { "socket": 4, "start": 0, "end": 20.000215, "seconds": 20.000215, "bytes": 221415128, "bits_per_second": 88565098.888017 } }], "sum_sent": { "start": 0, "end": 20.000215, "seconds": 20.000215, "bytes": 235230824, "bits_per_second": 94091317.866364, "retransmits": 686 }, "sum_received": { "start": 0, "end": 20.000215, "seconds": 20.000215, "bytes": 221415128, "bits_per_second": 88565098.888017 }, "cpu_utilization_percent": { "host_total": 0.957782, "host_user": 0.038625, "host_system": 0.907690, "remote_total": 5.297520, "remote_user": 0, "remote_system": 5.307290 }, "sender_tcp_congestion": "htcp" } } """ result = parse_output(test_output.split("\n")) pprint.PrettyPrinter(indent=4).pprint(result) test_output = """ { "start" : { "connected": [{ "socket": 4, "local_host": "150.254.208.65", "local_port": 40574, "remote_host": "140.182.44.177", "remote_port": 5201 }], "version": "iperf 3.1.6", "system_info": "Linux ps-4-0 4.4.0-59-generic #80~14.04.1-Ubuntu SMP Fri Jan 6 18:02:02 UTC 2017 x86_64", "timestamp": { "time": "Mon, 13 Feb 2017 19:29:01 GMT", "timesecs": 1487014141 }, "connecting_to": { "host": "140.182.44.177", "port": 5201 }, "cookie": "ps-4-0.1487014141.570141.2f10aa7723f", "tcp_mss_default": 1448, "test_start": { "protocol": "TCP", "num_streams": 1, "blksize": 131072, "omit": 0, "duration": 20, "bytes": 0, "blocks": 0, "reverse": 0 } }, "intervals": [{ "streams": [{ "socket": 4, "start": 0, "end": 1.000098, "seconds": 1.000098, "bytes": 2114080, "bits_per_second": 16910982.892177, "retransmits": 0, "snd_cwnd": 304080, "rtt": 134421, "omitted": false }], "sum": { "start": 0, "end": 1.000098, "seconds": 1.000098, "bytes": 2114080, "bits_per_second": 16910982.892177, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 1.000098, "end": 2.000288, "seconds": 1.000190, "bytes": 2150280, "bits_per_second": 17198971.858117, "retransmits": 35, "snd_cwnd": 130320, "rtt": 133798, "omitted": false }], "sum": { "start": 1.000098, "end": 2.000288, "seconds": 1.000190, "bytes": 2150280, "bits_per_second": 17198971.858117, "retransmits": 35, "omitted": false } }, { "streams": [{ "socket": 4, "start": 2.000288, "end": 3.000341, "seconds": 1.000053, "bytes": 1042560, "bits_per_second": 8340038.570728, "retransmits": 0, "snd_cwnd": 144800, "rtt": 133840, "omitted": false }], "sum": { "start": 2.000288, "end": 3.000341, "seconds": 1.000053, "bytes": 1042560, "bits_per_second": 8340038.570728, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 3.000341, "end": 4.000411, "seconds": 1.000070, "bytes": 1042560, "bits_per_second": 8339897.402759, "retransmits": 0, "snd_cwnd": 215752, "rtt": 138897, "omitted": false }], "sum": { "start": 3.000341, "end": 4.000411, "seconds": 1.000070, "bytes": 1042560, "bits_per_second": 8339897.402759, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 4.000411, "end": 5.000199, "seconds": 0.999788, "bytes": 2085120, "bits_per_second": 16684496.347688, "retransmits": 0, "snd_cwnd": 354760, "rtt": 133983, "omitted": false }], "sum": { "start": 4.000411, "end": 5.000199, "seconds": 0.999788, "bytes": 2085120, "bits_per_second": 16684496.347688, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 5.000199, "end": 6.000137, "seconds": 0.999938, "bytes": 3258000, "bits_per_second": 26065615.777040, "retransmits": 0, "snd_cwnd": 563272, "rtt": 133985, "omitted": false }], "sum": { "start": 5.000199, "end": 6.000137, "seconds": 0.999938, "bytes": 3258000, "bits_per_second": 26065615.777040, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 6.000137, "end": 7.000188, "seconds": 1.000051, "bytes": 5170200, "bits_per_second": 41359489.773652, "retransmits": 32, "snd_cwnd": 380824, "rtt": 134023, "omitted": false }], "sum": { "start": 6.000137, "end": 7.000188, "seconds": 1.000051, "bytes": 5170200, "bits_per_second": 41359489.773652, "retransmits": 32, "omitted": false } }, { "streams": [{ "socket": 4, "start": 7.000188, "end": 8.000114, "seconds": 0.999926, "bytes": 2621440, "bits_per_second": 20973070.114569, "retransmits": 0, "snd_cwnd": 390960, "rtt": 134016, "omitted": false }], "sum": { "start": 7.000188, "end": 8.000114, "seconds": 0.999926, "bytes": 2621440, "bits_per_second": 20973070.114569, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 8.000114, "end": 9.000442, "seconds": 1.000328, "bytes": 2621440, "bits_per_second": 20964647.253062, "retransmits": 0, "snd_cwnd": 480736, "rtt": 133858, "omitted": false }], "sum": { "start": 8.000114, "end": 9.000442, "seconds": 1.000328, "bytes": 2621440, "bits_per_second": 20964647.253062, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 9.000442, "end": 10.000102, "seconds": 0.999660, "bytes": 5242880, "bits_per_second": 41957304.849833, "retransmits": 0, "snd_cwnd": 695040, "rtt": 134062, "omitted": false }], "sum": { "start": 9.000442, "end": 10.000102, "seconds": 0.999660, "bytes": 5242880, "bits_per_second": 41957304.849833, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 10.000102, "end": 11.000162, "seconds": 1.000060, "bytes": 6553600, "bits_per_second": 52425650.189245, "retransmits": 0, "snd_cwnd": 986088, "rtt": 134923, "omitted": false }], "sum": { "start": 10.000102, "end": 11.000162, "seconds": 1.000060, "bytes": 6553600, "bits_per_second": 52425650.189245, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 11.000162, "end": 12.000334, "seconds": 1.000172, "bytes": 5242880, "bits_per_second": 41935821.242624, "retransmits": 199, "snd_cwnd": 279464, "rtt": 134194, "omitted": false }], "sum": { "start": 11.000162, "end": 12.000334, "seconds": 1.000172, "bytes": 5242880, "bits_per_second": 41935821.242624, "retransmits": 199, "omitted": false } }, { "streams": [{ "socket": 4, "start": 12.000334, "end": 13.000138, "seconds": 0.999804, "bytes": 2621440, "bits_per_second": 20975635.807598, "retransmits": 0, "snd_cwnd": 293944, "rtt": 133866, "omitted": false }], "sum": { "start": 12.000334, "end": 13.000138, "seconds": 0.999804, "bytes": 2621440, "bits_per_second": 20975635.807598, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 13.000138, "end": 14.000082, "seconds": 0.999944, "bytes": 2621440, "bits_per_second": 20972690.065278, "retransmits": 0, "snd_cwnd": 402544, "rtt": 134400, "omitted": false }], "sum": { "start": 13.000138, "end": 14.000082, "seconds": 0.999944, "bytes": 2621440, "bits_per_second": 20972690.065278, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 14.000082, "end": 15.000251, "seconds": 1.000169, "bytes": 2621440, "bits_per_second": 20967980.597452, "retransmits": 0, "snd_cwnd": 577752, "rtt": 137868, "omitted": false }], "sum": { "start": 14.000082, "end": 15.000251, "seconds": 1.000169, "bytes": 2621440, "bits_per_second": 20967980.597452, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 15.000251, "end": 16.000279, "seconds": 1.000028, "bytes": 2621440, "bits_per_second": 20970930.016598, "retransmits": 15, "snd_cwnd": 308424, "rtt": 134372, "omitted": false }], "sum": { "start": 15.000251, "end": 16.000279, "seconds": 1.000028, "bytes": 2621440, "bits_per_second": 20970930.016598, "retransmits": 15, "omitted": false } }, { "streams": [{ "socket": 4, "start": 16.000279, "end": 17.000356, "seconds": 1.000077, "bytes": 2621440, "bits_per_second": 20969905.124360, "retransmits": 0, "snd_cwnd": 360552, "rtt": 138924, "omitted": false }], "sum": { "start": 16.000279, "end": 17.000356, "seconds": 1.000077, "bytes": 2621440, "bits_per_second": 20969905.124360, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 17.000356, "end": 18.000418, "seconds": 1.000062, "bytes": 2621440, "bits_per_second": 20970220.080580, "retransmits": 0, "snd_cwnd": 524176, "rtt": 138088, "omitted": false }], "sum": { "start": 17.000356, "end": 18.000418, "seconds": 1.000062, "bytes": 2621440, "bits_per_second": 20970220.080580, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 18.000418, "end": 19.000208, "seconds": 0.999790, "bytes": 5242880, "bits_per_second": 41951851.850901, "retransmits": 0, "snd_cwnd": 836944, "rtt": 133874, "omitted": false }], "sum": { "start": 18.000418, "end": 19.000208, "seconds": 0.999790, "bytes": 5242880, "bits_per_second": 41951851.850901, "retransmits": 0, "omitted": false } }, { "streams": [{ "socket": 4, "start": 19.000208, "end": 20.000146, "seconds": 0.999938, "bytes": 7864320, "bits_per_second": 62918460.241771, "retransmits": 0, "snd_cwnd": 1206184, "rtt": 135744, "omitted": false }], "sum": { "start": 19.000208, "end": 20.000146, "seconds": 0.999938, "bytes": 7864320, "bits_per_second": 62918460.241771, "retransmits": 0, "omitted": false } }], "end": { "streams": [{ "sender": { "socket": 4, "start": 0, "end": 20.000146, "seconds": 20.000146, "bytes": 67980880, "bits_per_second": 27192153.616692, "retransmits": 281, "max_snd_cwnd": 1206184, "max_rtt": 138924, "min_rtt": 133798, "mean_rtt": 135056 }, "receiver": { "socket": 4, "start": 0, "end": 20.000146, "seconds": 20.000146, "bytes": 63723584, "bits_per_second": 25489247.640428 } }], "sum_sent": { "start": 0, "end": 20.000146, "seconds": 20.000146, "bytes": 67980880, "bits_per_second": 27192153.616692, "retransmits": 281 }, "sum_received": { "start": 0, "end": 20.000146, "seconds": 20.000146, "bytes": 63723584, "bits_per_second": 25489247.640428 }, "cpu_utilization_percent": { "host_total": 0.863500, "host_user": 0.115875, "host_system": 0.753187, "remote_total": 1.768670, "remote_user": 0.083237, "remote_system": 1.713290 }, "sender_tcp_congestion": "htcp" } } """ result = parse_output(test_output.split("\n")) pprint.PrettyPrinter(indent=4).pprint(result)

36.061617

122

0.32165

4,226

63,793

4.735447

0.160435

0.047222

0.087697

0.056966

0.827254

0.784829

0.772636

0.756446

0.730312

0.696532

0

0.262846

0.565893

63,793

1,768

123

36.082014

0.459791

0.008606

0

0.80758

0

0.002332

0.955749

0.005662

0

1

0.001166

false

0

0.002332

0

0.006997

0.002915

0

null

0

1

0

1

0

1

0

1

0

1

0

null

0

11

026bd6425a9781d510891eb67dbd33f576ab28a3

507

py

Python

2020-04-13/test_obj.py

feieryouyiji/learningpy

e110ec72ec3e4246b5195028776cdbaa22d25678

[ "MIT" ]

null

2020-04-13/test_obj.py

feieryouyiji/learningpy

e110ec72ec3e4246b5195028776cdbaa22d25678

[ "MIT" ]

null

2020-04-13/test_obj.py

feieryouyiji/learningpy

e110ec72ec3e4246b5195028776cdbaa22d25678

[ "MIT" ]

null

# class Student(object): # def __init__(self, name, score): # self.name = name # self.score = score # def print_score(self): # print('%s: %s' % (self.name, self.score)) class Student(object): def __init__(self, name, score): self.__name = name self.__score = score def print_score(self): print('%s: %s' % (self.__name, self.__score)) fyp = Student('fyp', 59) print("fyp===>", fyp) print("fyp===>", fyp.name) print("fyp===>", fyp.score)

21.125

53

0.56213

65

507

4.107692

0.184615

0.179775

0.194757

0.157303

0.786517

0

0.005236

0.246548

507

23

54

22.043478

0.693717

0.370809

0

0.096154

0

1

0.2

false

0

0.3

0.5

0

null

0

1

0

1

0

null

0

1

0

7

5a2c175a5b2e6eb67909e91d420d3ee8763cbd8c

31,117

py

Python

packages/fetchai/protocols/state_update/state_update_pb2.py

marcofavorito/agents-aea

e520f2f5d076a193514e194d94aa76c6423ac5bc

[ "Apache-2.0" ]

13

2020-11-13T11:29:46.000Z

2021-11-29T18:29:41.000Z

packages/fetchai/protocols/state_update/state_update_pb2.py

marcofavorito/agents-aea

e520f2f5d076a193514e194d94aa76c6423ac5bc

[ "Apache-2.0" ]

7

2020-11-13T10:37:16.000Z

2020-12-21T08:08:12.000Z

packages/fetchai/protocols/state_update/state_update_pb2.py

marcofavorito/agents-aea

e520f2f5d076a193514e194d94aa76c6423ac5bc

[ "Apache-2.0" ]

4

2020-11-27T20:50:09.000Z

2021-11-30T16:36:29.000Z

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: state_update.proto from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() DESCRIPTOR = _descriptor.FileDescriptor( name="state_update.proto", package="aea.fetchai.state_update", syntax="proto3", serialized_options=None, serialized_pb=b'\n\x12state_update.proto\x12\x18\x61\x65\x61.fetchai.state_update"\xd2\x0b\n\x12StateUpdateMessage\x12P\n\x05\x61pply\x18\x05 \x01(\x0b\x32?.aea.fetchai.state_update.StateUpdateMessage.Apply_PerformativeH\x00\x12L\n\x03\x65nd\x18\x06 \x01(\x0b\x32=.aea.fetchai.state_update.StateUpdateMessage.End_PerformativeH\x00\x12Z\n\ninitialize\x18\x07 \x01(\x0b\x32\x44.aea.fetchai.state_update.StateUpdateMessage.Initialize_PerformativeH\x00\x1a\x9e\x06\n\x17Initialize_Performative\x12\x8c\x01\n\x1e\x65xchange_params_by_currency_id\x18\x01 \x03(\x0b\x32\x64.aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.ExchangeParamsByCurrencyIdEntry\x12\x82\x01\n\x19utility_params_by_good_id\x18\x02 \x03(\x0b\x32_.aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.UtilityParamsByGoodIdEntry\x12{\n\x15\x61mount_by_currency_id\x18\x03 \x03(\x0b\x32\\.aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.AmountByCurrencyIdEntry\x12{\n\x15quantities_by_good_id\x18\x04 \x03(\x0b\x32\\.aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.QuantitiesByGoodIdEntry\x1a\x41\n\x1f\x45xchangeParamsByCurrencyIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x02:\x02\x38\x01\x1a<\n\x1aUtilityParamsByGoodIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x02:\x02\x38\x01\x1a\x39\n\x17\x41mountByCurrencyIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x05:\x02\x38\x01\x1a\x39\n\x17QuantitiesByGoodIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x05:\x02\x38\x01\x1a\xfa\x02\n\x12\x41pply_Performative\x12v\n\x15\x61mount_by_currency_id\x18\x01 \x03(\x0b\x32W.aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.AmountByCurrencyIdEntry\x12v\n\x15quantities_by_good_id\x18\x02 \x03(\x0b\x32W.aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.QuantitiesByGoodIdEntry\x1a\x39\n\x17\x41mountByCurrencyIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x05:\x02\x38\x01\x1a\x39\n\x17QuantitiesByGoodIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x05:\x02\x38\x01\x1a\x12\n\x10\x45nd_PerformativeB\x0e\n\x0cperformativeb\x06proto3', ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_EXCHANGEPARAMSBYCURRENCYIDENTRY = _descriptor.Descriptor( name="ExchangeParamsByCurrencyIdEntry", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.ExchangeParamsByCurrencyIdEntry", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="key", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.ExchangeParamsByCurrencyIdEntry.key", index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode("utf-8"), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="value", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.ExchangeParamsByCurrencyIdEntry.value", index=1, number=2, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=b"8\001", is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=877, serialized_end=942, ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_UTILITYPARAMSBYGOODIDENTRY = _descriptor.Descriptor( name="UtilityParamsByGoodIdEntry", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.UtilityParamsByGoodIdEntry", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="key", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.UtilityParamsByGoodIdEntry.key", index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode("utf-8"), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="value", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.UtilityParamsByGoodIdEntry.value", index=1, number=2, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=b"8\001", is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=944, serialized_end=1004, ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY = _descriptor.Descriptor( name="AmountByCurrencyIdEntry", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.AmountByCurrencyIdEntry", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="key", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.AmountByCurrencyIdEntry.key", index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode("utf-8"), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="value", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.AmountByCurrencyIdEntry.value", index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=b"8\001", is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=1006, serialized_end=1063, ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_QUANTITIESBYGOODIDENTRY = _descriptor.Descriptor( name="QuantitiesByGoodIdEntry", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.QuantitiesByGoodIdEntry", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="key", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.QuantitiesByGoodIdEntry.key", index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode("utf-8"), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="value", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.QuantitiesByGoodIdEntry.value", index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=b"8\001", is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=1065, serialized_end=1122, ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE = _descriptor.Descriptor( name="Initialize_Performative", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="exchange_params_by_currency_id", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.exchange_params_by_currency_id", index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="utility_params_by_good_id", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.utility_params_by_good_id", index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="amount_by_currency_id", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.amount_by_currency_id", index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="quantities_by_good_id", full_name="aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.quantities_by_good_id", index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[ _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_EXCHANGEPARAMSBYCURRENCYIDENTRY, _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_UTILITYPARAMSBYGOODIDENTRY, _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY, _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_QUANTITIESBYGOODIDENTRY, ], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=324, serialized_end=1122, ) _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY = _descriptor.Descriptor( name="AmountByCurrencyIdEntry", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.AmountByCurrencyIdEntry", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="key", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.AmountByCurrencyIdEntry.key", index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode("utf-8"), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="value", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.AmountByCurrencyIdEntry.value", index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=b"8\001", is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=1006, serialized_end=1063, ) _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_QUANTITIESBYGOODIDENTRY = _descriptor.Descriptor( name="QuantitiesByGoodIdEntry", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.QuantitiesByGoodIdEntry", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="key", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.QuantitiesByGoodIdEntry.key", index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode("utf-8"), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="value", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.QuantitiesByGoodIdEntry.value", index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[], enum_types=[], serialized_options=b"8\001", is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=1065, serialized_end=1122, ) _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE = _descriptor.Descriptor( name="Apply_Performative", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="amount_by_currency_id", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.amount_by_currency_id", index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="quantities_by_good_id", full_name="aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.quantities_by_good_id", index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[ _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY, _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_QUANTITIESBYGOODIDENTRY, ], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=1125, serialized_end=1503, ) _STATEUPDATEMESSAGE_END_PERFORMATIVE = _descriptor.Descriptor( name="End_Performative", full_name="aea.fetchai.state_update.StateUpdateMessage.End_Performative", filename=None, file=DESCRIPTOR, containing_type=None, fields=[], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=1505, serialized_end=1523, ) _STATEUPDATEMESSAGE = _descriptor.Descriptor( name="StateUpdateMessage", full_name="aea.fetchai.state_update.StateUpdateMessage", filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name="apply", full_name="aea.fetchai.state_update.StateUpdateMessage.apply", index=0, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="end", full_name="aea.fetchai.state_update.StateUpdateMessage.end", index=1, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), _descriptor.FieldDescriptor( name="initialize", full_name="aea.fetchai.state_update.StateUpdateMessage.initialize", index=2, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, ), ], extensions=[], nested_types=[ _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE, _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE, _STATEUPDATEMESSAGE_END_PERFORMATIVE, ], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name="performative", full_name="aea.fetchai.state_update.StateUpdateMessage.performative", index=0, containing_type=None, fields=[], ), ], serialized_start=49, serialized_end=1539, ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_EXCHANGEPARAMSBYCURRENCYIDENTRY.containing_type = ( _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_UTILITYPARAMSBYGOODIDENTRY.containing_type = ( _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY.containing_type = ( _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_QUANTITIESBYGOODIDENTRY.containing_type = ( _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE.fields_by_name[ "exchange_params_by_currency_id" ].message_type = ( _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_EXCHANGEPARAMSBYCURRENCYIDENTRY ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE.fields_by_name[ "utility_params_by_good_id" ].message_type = _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_UTILITYPARAMSBYGOODIDENTRY _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE.fields_by_name[ "amount_by_currency_id" ].message_type = _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE.fields_by_name[ "quantities_by_good_id" ].message_type = _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_QUANTITIESBYGOODIDENTRY _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE.containing_type = _STATEUPDATEMESSAGE _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY.containing_type = ( _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE ) _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_QUANTITIESBYGOODIDENTRY.containing_type = ( _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE ) _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE.fields_by_name[ "amount_by_currency_id" ].message_type = _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE.fields_by_name[ "quantities_by_good_id" ].message_type = _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_QUANTITIESBYGOODIDENTRY _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE.containing_type = _STATEUPDATEMESSAGE _STATEUPDATEMESSAGE_END_PERFORMATIVE.containing_type = _STATEUPDATEMESSAGE _STATEUPDATEMESSAGE.fields_by_name[ "apply" ].message_type = _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE _STATEUPDATEMESSAGE.fields_by_name[ "end" ].message_type = _STATEUPDATEMESSAGE_END_PERFORMATIVE _STATEUPDATEMESSAGE.fields_by_name[ "initialize" ].message_type = _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE _STATEUPDATEMESSAGE.oneofs_by_name["performative"].fields.append( _STATEUPDATEMESSAGE.fields_by_name["apply"] ) _STATEUPDATEMESSAGE.fields_by_name[ "apply" ].containing_oneof = _STATEUPDATEMESSAGE.oneofs_by_name["performative"] _STATEUPDATEMESSAGE.oneofs_by_name["performative"].fields.append( _STATEUPDATEMESSAGE.fields_by_name["end"] ) _STATEUPDATEMESSAGE.fields_by_name[ "end" ].containing_oneof = _STATEUPDATEMESSAGE.oneofs_by_name["performative"] _STATEUPDATEMESSAGE.oneofs_by_name["performative"].fields.append( _STATEUPDATEMESSAGE.fields_by_name["initialize"] ) _STATEUPDATEMESSAGE.fields_by_name[ "initialize" ].containing_oneof = _STATEUPDATEMESSAGE.oneofs_by_name["performative"] DESCRIPTOR.message_types_by_name["StateUpdateMessage"] = _STATEUPDATEMESSAGE _sym_db.RegisterFileDescriptor(DESCRIPTOR) StateUpdateMessage = _reflection.GeneratedProtocolMessageType( "StateUpdateMessage", (_message.Message,), { "Initialize_Performative": _reflection.GeneratedProtocolMessageType( "Initialize_Performative", (_message.Message,), { "ExchangeParamsByCurrencyIdEntry": _reflection.GeneratedProtocolMessageType( "ExchangeParamsByCurrencyIdEntry", (_message.Message,), { "DESCRIPTOR": _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_EXCHANGEPARAMSBYCURRENCYIDENTRY, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.ExchangeParamsByCurrencyIdEntry) }, ), "UtilityParamsByGoodIdEntry": _reflection.GeneratedProtocolMessageType( "UtilityParamsByGoodIdEntry", (_message.Message,), { "DESCRIPTOR": _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_UTILITYPARAMSBYGOODIDENTRY, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.UtilityParamsByGoodIdEntry) }, ), "AmountByCurrencyIdEntry": _reflection.GeneratedProtocolMessageType( "AmountByCurrencyIdEntry", (_message.Message,), { "DESCRIPTOR": _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.AmountByCurrencyIdEntry) }, ), "QuantitiesByGoodIdEntry": _reflection.GeneratedProtocolMessageType( "QuantitiesByGoodIdEntry", (_message.Message,), { "DESCRIPTOR": _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_QUANTITIESBYGOODIDENTRY, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative.QuantitiesByGoodIdEntry) }, ), "DESCRIPTOR": _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.Initialize_Performative) }, ), "Apply_Performative": _reflection.GeneratedProtocolMessageType( "Apply_Performative", (_message.Message,), { "AmountByCurrencyIdEntry": _reflection.GeneratedProtocolMessageType( "AmountByCurrencyIdEntry", (_message.Message,), { "DESCRIPTOR": _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.AmountByCurrencyIdEntry) }, ), "QuantitiesByGoodIdEntry": _reflection.GeneratedProtocolMessageType( "QuantitiesByGoodIdEntry", (_message.Message,), { "DESCRIPTOR": _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_QUANTITIESBYGOODIDENTRY, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.Apply_Performative.QuantitiesByGoodIdEntry) }, ), "DESCRIPTOR": _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.Apply_Performative) }, ), "End_Performative": _reflection.GeneratedProtocolMessageType( "End_Performative", (_message.Message,), { "DESCRIPTOR": _STATEUPDATEMESSAGE_END_PERFORMATIVE, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage.End_Performative) }, ), "DESCRIPTOR": _STATEUPDATEMESSAGE, "__module__": "state_update_pb2" # @@protoc_insertion_point(class_scope:aea.fetchai.state_update.StateUpdateMessage) }, ) _sym_db.RegisterMessage(StateUpdateMessage) _sym_db.RegisterMessage(StateUpdateMessage.Initialize_Performative) _sym_db.RegisterMessage( StateUpdateMessage.Initialize_Performative.ExchangeParamsByCurrencyIdEntry ) _sym_db.RegisterMessage( StateUpdateMessage.Initialize_Performative.UtilityParamsByGoodIdEntry ) _sym_db.RegisterMessage( StateUpdateMessage.Initialize_Performative.AmountByCurrencyIdEntry ) _sym_db.RegisterMessage( StateUpdateMessage.Initialize_Performative.QuantitiesByGoodIdEntry ) _sym_db.RegisterMessage(StateUpdateMessage.Apply_Performative) _sym_db.RegisterMessage(StateUpdateMessage.Apply_Performative.AmountByCurrencyIdEntry) _sym_db.RegisterMessage(StateUpdateMessage.Apply_Performative.QuantitiesByGoodIdEntry) _sym_db.RegisterMessage(StateUpdateMessage.End_Performative) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_EXCHANGEPARAMSBYCURRENCYIDENTRY._options = ( None ) _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_UTILITYPARAMSBYGOODIDENTRY._options = None _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY._options = None _STATEUPDATEMESSAGE_INITIALIZE_PERFORMATIVE_QUANTITIESBYGOODIDENTRY._options = None _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_AMOUNTBYCURRENCYIDENTRY._options = None _STATEUPDATEMESSAGE_APPLY_PERFORMATIVE_QUANTITIESBYGOODIDENTRY._options = None # @@protoc_insertion_point(module_scope)

38.368681

2,250

0.663239

2,777

31,117

7.062297

0.067339

0.030186

0.138691

0.05568

0.845758

0.795074

0.740873

0.703192

0.618397

0.609678

0

0.027626

0.25086

31,117

810

2,251

38.416049

0.813693

0.043288

0

0.738065

1

0.00129

0.221348

0.191604

0

1

0

false

0

0.005161

0

0.005161

0

null

0

1

0

1

0

1

0

1

0

null

0

8

5a2d64ae674181120650cec41529448f519e7c64

45

py

Python

LogSystem_JE/venv/Lib/site-packages/JELogSystem/__init__.py

JE-Chen/je_old_repo

a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5

[ "MIT" ]

3

2020-12-21T03:59:11.000Z

2020-12-30T07:27:47.000Z

LogSystem_JE/venv/Lib/site-packages/JELogSystem/__init__.py

JE-Chen/je_old_repo

a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5

[ "MIT" ]

null

LogSystem_JE/venv/Lib/site-packages/JELogSystem/__init__.py

JE-Chen/je_old_repo

a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5

[ "MIT" ]

null

from JELogSystem.Log_System import Log_System

45

0.911111

7

45

5.571429

0.714286

0.461538

0

0.066667

45

1

45

0.928571

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

5a38b7bad01c4cc0ca6d76787a3d503597e99deb

9,108

py

Python

appengine/chromium_build/tests/console_test.py

mithro/chromium-infra

d27ac0b230bedae4bc968515b02927cf9e17c2b7

[ "BSD-3-Clause" ]

2

2021-04-13T21:22:18.000Z

2021-09-07T02:11:57.000Z

appengine/chromium_build/tests/console_test.py

mithro/chromium-infra

d27ac0b230bedae4bc968515b02927cf9e17c2b7

[ "BSD-3-Clause" ]

21

2020-09-06T02:41:05.000Z

2022-03-02T04:40:01.000Z

appengine/chromium_build/tests/console_test.py

mithro/chromium-infra

d27ac0b230bedae4bc968515b02927cf9e17c2b7

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # Copyright (c) 2015 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import app from tests import cb class ConsoleTestCase(cb.CbTestCase): def test_console_handler(self): self.save_page(localpath='chromium/sheriff.js', content='document.write(\'sheriff1\')') self.save_page(localpath='chromium/sheriff_webkit.js', content='document.write(\'sheriff2\')') self.save_page(localpath='chromium/sheriff_memory.js', content='document.write(\'sheriff3\')') self.save_page(localpath='chromium/sheriff_nacl.js', content='document.write(\'sheriff4\')') self.save_page(localpath='chromium/sheriff_perf.js', content='document.write(\'sheriff5\')') self.save_page(localpath='chromium/sheriff_cros_mtv.js', content='document.write(\'sheriff6, sheriff7\')') self.save_page(localpath='chromium/sheriff_cros_nonmtv.js', content='document.write(\'sheriff8\')') exp_console = self.read_file('exp_console.html') in_console = {'content': self.read_file('in_console.html')} act_console = app.console_handler( unquoted_localpath='chromium/console', remoteurl='http://build.chromium.org/p/chromium/console', page_data=in_console)['content'] # Uncomment if deeper inspection is needed of the returned console. # This is also useful if changing the site layout and you need to # 'retrain' the test expectations. # self.write_file('exp_console.html', act_console) self.assertEquals(exp_console, act_console, 'Unexpected console output found') def test_console_handler_utf8(self): self.save_page(localpath='chromium/sheriff.js', content='document.write(\'sheriff1\')') self.save_page(localpath='chromium/sheriff_webkit.js', content='document.write(\'sheriff2\')') self.save_page(localpath='chromium/sheriff_memory.js', content='document.write(\'sheriff3\')') self.save_page(localpath='chromium/sheriff_nacl.js', content='document.write(\'sheriff4\')') self.save_page(localpath='chromium/sheriff_perf.js', content='document.write(\'sheriff5\')') self.save_page(localpath='chromium/sheriff_cros_mtv.js', content='document.write(\'sheriff6, sheriff7\')') self.save_page(localpath='chromium/sheriff_cros_nonmtv.js', content='document.write(\'sheriff8\')') exp_console = self.read_file('exp_console.html') in_console = {'content': self.read_file('in_console.html')} act_console = app.console_handler( unquoted_localpath='chromium/console', remoteurl='http://build.chromium.org/p/chromium/console', page_data=in_console)['content'] # Uncomment if deeper inspection is needed of the returned console. # This is also useful if changing the site layout and you need to # 'retrain' the test expectations. # self.write_file('exp_console.html', act_console) self.assertEquals(exp_console, act_console, 'Unexpected console output found') def test_parse_master(self): in_console = {'content': self.read_file('in_console.html')} app.parse_master( localpath='chromium/console', remoteurl='http://build.chromium.org/p/chromium/console', page_data=in_console) test_revision = '314671' rowdata = app.get_and_cache_rowdata('chromium/console/' + test_revision) summary = app.get_and_cache_pagedata('chromium/console/summary')['content'] act_row = {} exp_row = {} for item in ['rev', 'name', 'status', 'comment']: # We only want to test specific values in rowdata, so we create a new # hash that has just those values. act_row[item] = rowdata[item] # Uncomment if deeper inspection is needed of the returned console. # This is also useful if changing the site layout and you need to # 'retrain' the test expectations. # self.write_file('exp_%s.html' % item, # act_row[item].encode('utf-8')) # self.write_file('exp_summary.html', # summary.encode('utf-8')) exp_row[item] = self.read_file('exp_%s.html' % item).decode('utf-8') exp_summary = self.read_file('exp_summary.html').decode('utf-8') self.assertEquals(exp_row, act_row, 'Unexpected row data found') self.assertEquals(exp_summary, summary, 'Unexpected build summary found') def test_parse_master_utf8(self): in_console = {'content': self.read_file('in_console.html')} app.parse_master( localpath='chromium/console', remoteurl='http://build.chromium.org/p/chromium/console', page_data=in_console) test_revision = '314921' rowdata = app.get_and_cache_rowdata('chromium/console/' + test_revision) summary = app.get_and_cache_pagedata('chromium/console/summary')['content'] act_row = {} exp_row = {} for item in ['rev', 'name', 'status', 'comment']: # We only want to test specific values in rowdata, so we create a new # hash that has just those values. act_row[item] = rowdata[item] # Uncomment if deeper inspection is needed of the returned console. # This is also useful if changing the site layout and you need to # 'retrain' the test expectations. # self.write_file('exp_%s.html' % item, # act_row[item].encode('utf-8')) # self.write_file('exp_summary.html', # summary.encode('utf-8')) exp_row[item] = self.read_file('exp_%s.html' % item).decode('utf-8') exp_summary = self.read_file('exp_summary.html').decode('utf-8') self.assertEquals(exp_row, act_row, 'Unexpected row data found') self.assertEquals(exp_summary, summary, 'Unexpected build summary found') def test_console_merger(self): for master in ['linux', 'mac']: page_data = {'content': self.read_file('in_%s.html' % master)} app.parse_master( localpath='chromium.%s/console' % master, remoteurl='http://build.chromium.org/p/chromium.%s/console' % master, page_data=page_data) # Get the expected and real output, compare. app.console_merger( 'chromium/console', '', {}, masters_to_merge=[ 'chromium.linux', 'chromium.mac', ], num_rows_to_merge=20) actual_console = app.get_and_cache_pagedata('chromium/console')['content'] # Uncomment if deeper inspection is needed of the returned console. # import logging # logging.debug('foo') # self.write_file('exp_merged.html', actual_console) # import code # code.interact(local=locals()) self.assertEquals( self.read_file('exp_merged.html').decode('utf-8'), actual_console, 'Unexpected console output found') def test_console_merger_splitrevs(self): for master in ['linux', 'mac']: page_data = {'content': self.read_file('in_%s.html' % master)} app.parse_master( localpath='chromium.%s/console' % master, remoteurl='http://build.chromium.org/p/chromium.%s/console' % master, page_data=page_data) # Get the expected and real output, compare. app.console_merger( 'chromium/console', '', {}, masters_to_merge=[ 'chromium.linux', 'chromium.mac', ], num_rows_to_merge=20) act_merged = app.get_and_cache_pagedata('chromium/console')['content'] # Uncomment if deeper inspection is needed of the returned console. # import logging # logging.debug('foo') # self.write_file('exp_merged.html', act_merged) # import code # code.interact(local=locals()) self.assertEquals(self.read_file('exp_merged.html'), act_merged, 'Unexpected console output found') def test_console_utf8_devcomment(self): """Test that a console DevComment row with a UTF-8 character is retained.""" for master in ['mac']: page_data = {'content': self.read_file('in_%s.html' % master)} app.parse_master( localpath='chromium.%s/console' % master, remoteurl='http://build.chromium.org/p/chromium.%s/console' % master, page_data=page_data) # Get the expected and real output, compare. app.console_merger( 'chromium/console', '', {}, masters_to_merge=[ 'chromium.mac', ], num_rows_to_merge=20) act_merged = app.get_and_cache_pagedata('chromium/console')['content'] # Uncomment if deeper inspection is needed of the returned console. # import logging # logging.debug('foo') # self.write_file('exp_merged.html', act_merged.encode('utf-8')) # import code # code.interact(local=locals()) self.assertEquals(self.read_file('exp_merged.html').decode('utf-8'), act_merged, 'Unexpected console output found')

42.760563

80

0.653931

1,141

9,108

5.037686

0.137599

0.062109

0.033403

0.051148

0.933194

0.926061

0.918058

0.910752

0.901009

0

0.007424

0.216184

9,108

212

81

42.962264

0.797731

0.246926

0

0.850746

0

0.287961

0.0538

0

0.067164

1

0.052239

false

0

0.014925

0

0.074627

0

null

0

1

0

1

0

null

0

7

ce6ae01da7798e7fc4817a6c05f5685a2879cdaa

3,925

py

Python

trello/lists.py

glitchdotcom/trello-py

3fea701fbac389306b6f36641fd8e39303df7e91

[ "BSD-2-Clause" ]

1

2020-05-21T22:12:36.000Z

lists.py

Caloba1/trello-api-py

03fede65b8bf4cd1b13ee685a1e5e21bcf2fbf57

[ "MIT" ]

null

lists.py

Caloba1/trello-api-py

03fede65b8bf4cd1b13ee685a1e5e21bcf2fbf57

[ "MIT" ]

2

2015-11-19T22:26:57.000Z

2019-10-22T19:34:15.000Z

import json import requests class Lists(object): __module__ = 'trello' def __init__(self, apikey, token=None): self._apikey = apikey self._token = token def get(self, list_id, cards=None, card_fields=None, fields=None): resp = requests.get("https://trello.com/1/lists/%s" % (list_id), params=dict(key=self._apikey, token=self._token, cards=cards, card_fields=card_fields, fields=fields), data=None) resp.raise_for_status() return json.loads(resp.content) def get_field(self, field, list_id): resp = requests.get("https://trello.com/1/lists/%s/%s" % (list_id, field), params=dict(key=self._apikey, token=self._token), data=None) resp.raise_for_status() return json.loads(resp.content) def get_action(self, list_id, filter=None, fields=None, limit=None, page=None, idModels=None): resp = requests.get("https://trello.com/1/lists/%s/actions" % (list_id), params=dict(key=self._apikey, token=self._token, filter=filter, fields=fields, limit=limit, page=page, idModels=idModels), data=None) resp.raise_for_status() return json.loads(resp.content) def get_board(self, list_id, fields=None): resp = requests.get("https://trello.com/1/lists/%s/board" % (list_id), params=dict(key=self._apikey, token=self._token, fields=fields), data=None) resp.raise_for_status() return json.loads(resp.content) def get_board_field(self, field, list_id): resp = requests.get("https://trello.com/1/lists/%s/board/%s" % (list_id, field), params=dict(key=self._apikey, token=self._token), data=None) resp.raise_for_status() return json.loads(resp.content) def get_card(self, list_id, actions=None, attachments=None, members=None, checkItemStates=None, checklists=None, filter=None, fields=None): resp = requests.get("https://trello.com/1/lists/%s/cards" % (list_id), params=dict(key=self._apikey, token=self._token, actions=actions, attachments=attachments, members=members, checkItemStates=checkItemStates, checklists=checklists, filter=filter, fields=fields), data=None) resp.raise_for_status() return json.loads(resp.content) def get_card_filter(self, filter, list_id): resp = requests.get("https://trello.com/1/lists/%s/cards/%s" % (list_id, filter), params=dict(key=self._apikey, token=self._token), data=None) resp.raise_for_status() return json.loads(resp.content) def update(self, list_id, name=None, closed=None): resp = requests.put("https://trello.com/1/lists/%s" % (list_id), params=dict(key=self._apikey, token=self._token), data=dict(name=name, closed=closed)) resp.raise_for_status() return json.loads(resp.content) def update_closed(self, list_id, value): resp = requests.put("https://trello.com/1/lists/%s/closed" % (list_id), params=dict(key=self._apikey, token=self._token), data=dict(value=value)) resp.raise_for_status() return json.loads(resp.content) def update_name(self, list_id, value): resp = requests.put("https://trello.com/1/lists/%s/name" % (list_id), params=dict(key=self._apikey, token=self._token), data=dict(value=value)) resp.raise_for_status() return json.loads(resp.content) def new(self, name, idBoard): resp = requests.post("https://trello.com/1/lists" % (), params=dict(key=self._apikey, token=self._token), data=dict(name=name, idBoard=idBoard)) resp.raise_for_status() return json.loads(resp.content) def new_card(self, list_id, name, desc=None): resp = requests.post("https://trello.com/1/lists/%s/cards" % (list_id), params=dict(key=self._apikey, token=self._token), data=dict(name=name, desc=desc)) resp.raise_for_status() return json.loads(resp.content)

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0.673121

558

3,925

4.566308

0.100358

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null

0

1

0

1

0

7

ce6b918c8145176731e624a4e63fc9b99437bde1

145

py

Python

geekshop/mainapp/admin.py

PorcupineVN/interner-store

c19a26d79933f41ba4f2a8df69bd386c4ba168a8

[ "MIT" ]

null

geekshop/mainapp/admin.py

PorcupineVN/interner-store

c19a26d79933f41ba4f2a8df69bd386c4ba168a8

[ "MIT" ]

1

2022-02-09T07:29:04.000Z

geekshop/mainapp/admin.py

Deathless47/Internet-store

09b1fa631295bcc9e12fc2c8dfbb7b027cac73ed

[ "MIT" ]

null

from django.contrib import admin from .models import Product, ProductCategory admin.site.register(ProductCategory) admin.site.register(Product)

24.166667

44

0.841379

18

145

6.777778

0.555556

0.327869

0.393443

0.52459

0

0.082759

145

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null

0

1

0

1

0

7

ceb93c335c07601f33ad16d0e61ea063167165bd

3,921

py

Python

tests/test_composition_measurement.py

IBPA/FoodAtlas

0a431f0a391adaa8984b380f3f6f7189f27b9311

[ "Apache-2.0" ]

1

2022-02-07T10:04:35.000Z

tests/test_composition_measurement.py

IBPA/FoodAtlas

0a431f0a391adaa8984b380f3f6f7189f27b9311

[ "Apache-2.0" ]

null

tests/test_composition_measurement.py

IBPA/FoodAtlas

0a431f0a391adaa8984b380f3f6f7189f27b9311

[ "Apache-2.0" ]

null

import pytest from food_ke.composition_measurement import CompositionMeasurement class TestCompositionMeasurement: @pytest.mark.parametrize( "a,b", [ ( CompositionMeasurement( food_name="cocoa", constituent_name="epicatechin", central_tendency_measurement=1.0, variance_measurement=0.1, units="mg/kg", ), CompositionMeasurement( food_name="cocoa", constituent_name="epicatechin", central_tendency_measurement=1.0, variance_measurement=0.1, units="mg/kg", ), ), ( CompositionMeasurement( food_name="cocoa", constituent_name="epicatechin", central_tendency_measurement=1.0, variance_measurement=0.1, units=None, ), CompositionMeasurement( food_name="cocoa", constituent_name="epicatechin", central_tendency_measurement=1.0, variance_measurement=0.1, units=None, ), ), ( CompositionMeasurement( food_name="cocoa", constituent_name="epicatechin", central_tendency_measurement=1.0, variance_measurement=None, units=None, ), CompositionMeasurement( food_name="cocoa", constituent_name="epicatechin", central_tendency_measurement=1.0, variance_measurement=None, units=None, ), ), ( CompositionMeasurement( food_name="cocoa", constituent_name="epicatechin", central_tendency_measurement=1.0, variance_measurement=0.1, units=None, ), CompositionMeasurement( food_name="cocoa", constituent_name="epicatechin", central_tendency_measurement=1.0, variance_measurement=0.1, units=None, ), ), ( CompositionMeasurement( food_name=None, constituent_name=None, central_tendency_measurement=1.0, variance_measurement=None, units=None, ), CompositionMeasurement( food_name=None, constituent_name=None, central_tendency_measurement=1.0, variance_measurement=None, units=None, ), ), ], ) def test_eq(self, a, b): assert a == b @pytest.mark.parametrize( "a,b", [ ( CompositionMeasurement( food_name=None, constituent_name=None, central_tendency_measurement=47.0, variance_measurement=None, units=None, ), CompositionMeasurement( food_name=None, constituent_name=None, central_tendency_measurement=693.0, variance_measurement=None, units=None, ), ), ], ) def test_neq(self, a, b): assert not a == b assert not b == a

32.94958

66

0.429737

256

3,921

6.332031

0.140625

0.192474

0.222085

0.166564

0.90438

0.847008

0

0.019928

0.500893

3,921

118

67

33.228814

0.80838

0

0.824561

0

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0.026316

1

0.017544

false

0

0.017544

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0.04386

0

null

0

1

0

1

0

1

0

null

0

10

0c686020ac65f88973ba1ab57c9c2885bee6327a

4,368

py

Python

algorithms/spot_finding/threshold.py

toastisme/dials

6bc8ababc33bfe334513677f8adb65c0e90003f3

[ "BSD-3-Clause" ]

58

2015-10-15T09:28:20.000Z

2022-03-28T20:09:38.000Z

algorithms/spot_finding/threshold.py

toastisme/dials

6bc8ababc33bfe334513677f8adb65c0e90003f3

[ "BSD-3-Clause" ]

1,741

2015-11-24T08:17:02.000Z

2022-03-31T15:46:42.000Z

algorithms/spot_finding/threshold.py

toastisme/dials

6bc8ababc33bfe334513677f8adb65c0e90003f3

[ "BSD-3-Clause" ]

45

2015-10-14T13:44:16.000Z

2022-03-22T14:45:56.000Z

class ThresholdStrategy: """ Base class for spot finder threshold strategies. """ def __init__(self, **kwargs): """ Initialise with key word arguments. """ pass def __call__(self, image): """ Threshold the image. """ raise RuntimeError("Overload Me!") class DispersionThresholdStrategy(ThresholdStrategy): """ A class implementing a 'gain' threshold. """ def __init__(self, **kwargs): """ Set the threshold algorithm up """ # Initialise the base class ThresholdStrategy.__init__(self, **kwargs) # Get the parameters self._kernel_size = kwargs.get("kernel_size", (3, 3)) self._gain = kwargs.get("gain") self._n_sigma_b = kwargs.get("n_sigma_b", 6) self._n_sigma_s = kwargs.get("n_sigma_s", 3) self._min_count = kwargs.get("min_count", 2) self._threshold = kwargs.get("global_threshold", 0) # Save the constant gain self._gain_map = None # Create a buffer self.algorithm = {} def __call__(self, image, mask): """ Call the thresholding function :param image: The image to process :param mask: The mask to use :return: The thresholded image """ from dials.algorithms.image import threshold from dials.array_family import flex # Initialise the algorithm try: algorithm = self.algorithm[image.all()] except Exception: algorithm = threshold.DispersionThreshold( image.all(), self._kernel_size, self._n_sigma_b, self._n_sigma_s, self._threshold, self._min_count, ) self.algorithm[image.all()] = algorithm # Set the gain if self._gain is not None: assert self._gain > 0 self._gain_map = flex.double(image.accessor(), self._gain) self._gain = None # Compute the threshold result = flex.bool(flex.grid(image.all())) if self._gain_map: algorithm(image, mask, self._gain_map, result) else: algorithm(image, mask, result) # Return the result return result class DispersionExtendedThresholdStrategy(ThresholdStrategy): """ A class implementing a 'gain' threshold. """ def __init__(self, **kwargs): """ Set the threshold algorithm up """ # Initialise the base class ThresholdStrategy.__init__(self, **kwargs) # Get the parameters self._kernel_size = kwargs.get("kernel_size", (3, 3)) self._gain = kwargs.get("gain") self._n_sigma_b = kwargs.get("n_sigma_b", 6) self._n_sigma_s = kwargs.get("n_sigma_s", 3) self._min_count = kwargs.get("min_count", 2) self._threshold = kwargs.get("global_threshold", 0) # Save the constant gain self._gain_map = None # Create a buffer self.algorithm = {} def __call__(self, image, mask): """ Call the thresholding function :param image: The image to process :param mask: The mask to use :return: The thresholded image """ from dials.algorithms.image import threshold from dials.array_family import flex # Initialise the algorithm try: algorithm = self.algorithm[image.all()] except Exception: algorithm = threshold.DispersionExtendedThreshold( image.all(), self._kernel_size, self._n_sigma_b, self._n_sigma_s, self._threshold, self._min_count, ) self.algorithm[image.all()] = algorithm # Set the gain if self._gain is not None: assert self._gain > 0 self._gain_map = flex.double(image.accessor(), self._gain) self._gain = None # Compute the threshold result = flex.bool(flex.grid(image.all())) if self._gain_map: algorithm(image, mask, self._gain_map, result) else: algorithm(image, mask, result) # Return the result return result

28.180645

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0.564103

472

4,368

4.970339

0.184322

0.061381

0.034101

0.018755

0.875533

0

0.00487

0.341804

4,368

154

71

28.363636

0.81113

0.18956

0

0.87013

0

0.03887

0

0.025974

1

0.077922

false

0.012987

0.051948

0

0.194805

0

null

0

1

0

1

0

null

0

7

0cb5ef6c2f84e55ff2885c685786ca15de416654

9,505

py

Python

pdx-extract/tests/test_main.py

michaelheyman/PSU-Code-Review

5a55d981425aaad69dc9ee06baaaef22bc426893

[ "MIT" ]

null

pdx-extract/tests/test_main.py

michaelheyman/PSU-Code-Review

5a55d981425aaad69dc9ee06baaaef22bc426893

[ "MIT" ]

null

pdx-extract/tests/test_main.py

michaelheyman/PSU-Code-Review

5a55d981425aaad69dc9ee06baaaef22bc426893

[ "MIT" ]

null

import asyncio import unittest.mock as mock import asynctest import pytest from app import main from tests import data from tests import utils @mock.patch("requests.post") def test_authenticate_current_session_returns_ok(mock_requests): import requests term = {"code": "201904", "description": "Fall 2019 Quarter"} unique_session_id = "abcdef1234567890" cookies = {"JSESSIONID": "CF6813D3F9BFD1ABEEEF47E2FB094926"} response = requests.Response() response.status_code = requests.codes.ok mock_requests.return_value = response res = main.authenticate_current_session(term, unique_session_id, cookies) assert res.ok is True @mock.patch("requests.post") def test_authenticate_current_session_returns_not_ok_if_response_fails(mock_requests): import requests term = {"code": "201904", "description": "Fall 2019 Quarter"} unique_session_id = "abcdef1234567890" cookies = {"JSESSIONID": "CF6813D3F9BFD1ABEEEF47E2FB094926"} response = requests.Response() response.status_code = requests.codes.bad_request mock_requests.return_value = response res = main.authenticate_current_session(term, unique_session_id, cookies) assert res.ok is False @mock.patch("requests.get") def test_get_schedule_json_returns_ok_when_good_response(mock_requests): import json import requests subject = {"code": "CS", "description": "Computer Science"} term = {"code": "201904", "description": "Fall 2019 Quarter"} unique_session_id = "abcdef1234567890" cookies = {"JSESSIONID": "CF6813D3F9BFD1ABEEEF47E2FB094926"} response = requests.Response() response._content = bytearray(json.dumps(data.example_schedule), "utf-8") response.status_code = requests.codes.ok mock_requests.return_value = response schedule_json = main.get_schedule_json(subject, term, unique_session_id, cookies) assert schedule_json == data.example_schedule @mock.patch("requests.get") def test_get_schedule_json_returns_not_ok_when_bad_response(mock_requests): import requests subject = {"code": "CS", "description": "Computer Science"} term = {"code": "201904", "description": "Fall 2019 Quarter"} unique_session_id = "abcdef1234567890" cookies = {"JSESSIONID": "CF6813D3F9BFD1ABEEEF47E2FB094926"} response = requests.Response() response.status_code = requests.codes.bad_request mock_requests.return_value = response schedule_json = main.get_schedule_json(subject, term, unique_session_id, cookies) assert schedule_json is None @mock.patch("requests.get") def test_get_subjects_returns_json_response_when_response_ok(mock_requests): import json import requests cookies = {"cookie": "jar"} unique_session_id = "abcdef1234567890" term_date = "201904" subjects_response = [{"code": "ACTG", "description": "Accounting"}] response = requests.Response() response._content = bytearray(json.dumps(subjects_response), "utf-8") response.status_code = requests.codes.ok mock_requests.return_value = response subjects = main.get_subjects(cookies, unique_session_id, term_date) assert subjects == subjects_response @mock.patch("requests.get") def test_get_subjects_returns_none_when_response_ok(mock_requests): import json import requests cookies = {"cookie": "jar"} unique_session_id = "abcdef1234567890" term_date = "201904" subjects_response = [{"code": "ACTG", "description": "Accounting"}] response = requests.Response() response._content = bytearray(json.dumps(subjects_response), "utf-8") response.status_code = requests.codes.bad_request mock_requests.return_value = response subjects = main.get_subjects(cookies, unique_session_id, term_date) assert subjects is None @pytest.mark.asyncio @asynctest.patch("app.main.authenticate_current_session") @asynctest.patch("app.main.get_schedule_json") @asynctest.patch("app.pyppeteer.get_unique_session_id") async def test_get_subjects_json_returns_data( mock_get_unique_session_id, mock_get_schedule_json, mock_authenticate ): subjects = [ {"code": "ACTG", "description": "Accounting"}, {"code": "ACTG", "description": "Accounting"}, ] term = {"code": "201904", "description": "Fall 2019 Quarter"} cookies = {"cookie": "jar"} unique_session_id = "abcdef1234567890" mock_get_unique_session_id = asynctest.CoroutineMock() mock_get_unique_session_id = utils.set_async_result( mock_get_unique_session_id, unique_session_id ) mock_get_schedule_json.return_value = {"data": "foo"} subjects_json = await main.get_subjects_json(subjects, term, cookies, None) assert "foo" in subjects_json assert len(subjects_json) == 2 @pytest.mark.asyncio @asynctest.patch("app.main.authenticate_current_session") @asynctest.patch("app.main.get_schedule_json") @asynctest.patch("app.pyppeteer.get_unique_session_id") async def test_get_subjects_json_returns_none_when_no_data( mock_get_unique_session_id, mock_get_schedule_json, mock_authenticate ): subjects = [ {"code": "ACTG", "description": "Accounting"}, {"code": "ACTG", "description": "Accounting"}, ] term = {"code": "201904", "description": "Fall 2019 Quarter"} cookies = {"cookie": "jar"} unique_session_id = "abcdef1234567890" mock_get_unique_session_id = asynctest.CoroutineMock() mock_get_unique_session_id = utils.set_async_result( mock_get_unique_session_id, unique_session_id ) mock_get_schedule_json.return_value = {} subjects_json = await main.get_subjects_json(subjects, term, cookies, None) assert subjects_json == [] @mock.patch("requests.get") def test_get_terms_returns_json_response_when_response_ok(mock_requests): import json import requests cookies = {"cookie": "jar"} unique_session_id = "abcdef1234567890" terms_response = [{"code": "201904", "description": "Fall 2019 Quarter"}] response = requests.Response() response._content = bytearray(json.dumps(terms_response), "utf-8") response.status_code = requests.codes.ok mock_requests.return_value = response terms = main.get_terms(cookies, unique_session_id) assert terms == terms_response @mock.patch("requests.get") def test_get_terms_returns_none_when_response_not_ok(mock_requests): import json import requests cookies = {"cookie": "jar"} unique_session_id = "abcdef1234567890" terms_response = [{"code": "201904", "description": "Fall 2019 Quarter"}] response = requests.Response() response._content = bytearray(json.dumps(terms_response), "utf-8") response.status_code = requests.codes.bad_request mock_requests.return_value = response terms = main.get_terms(cookies, unique_session_id) assert terms is None @pytest.mark.asyncio @asynctest.patch("app.storage.upload_to_bucket") @asynctest.patch("app.main.get_terms") @asynctest.patch("app.pyppeteer.get_tokens") @asynctest.patch("app.pyppeteer.get_page") @asynctest.patch("app.pyppeteer.initialize") async def test_run_returns_empty_payload_when_no_results( mock_initialize, mock_get_page, mock_get_tokens, mock_get_terms, mock_upload_to_bucket, ): browser = asynctest.CoroutineMock() browser.close.return_value = asyncio.Future() browser.close.return_value.set_result(None) mock_initialize = utils.set_async_result(mock_initialize, browser) mock_get_page = utils.set_async_result(mock_get_page, None) mock_get_tokens.return_value = asyncio.Future() mock_get_tokens.return_value.set_result(["foo", "abcdef1234567890"]) mock_get_terms.return_value = [] mock_upload_to_bucket().return_value = None payload = await main.run() mock_initialize.assert_called mock_get_page.assert_called mock_get_tokens.assert_called mock_get_terms.assert_called mock_upload_to_bucket.assert_called assert payload == [] @pytest.mark.asyncio @asynctest.patch("app.storage.upload_to_bucket") @asynctest.patch("app.main.get_subjects_json") @asynctest.patch("app.main.get_subjects") @asynctest.patch("app.main.get_terms") @asynctest.patch("app.pyppeteer.get_tokens") @asynctest.patch("app.pyppeteer.get_page") @asynctest.patch("app.pyppeteer.initialize") async def test_run_returns_payload( mock_initialize, mock_get_page, mock_get_tokens, mock_get_terms, mock_get_subjects, mock_get_subjects_json, mock_upload_to_bucket, ): browser = asynctest.CoroutineMock() browser.close.return_value = asyncio.Future() browser.close.return_value.set_result(None) mock_initialize = utils.set_async_result(mock_initialize, browser) mock_get_page = utils.set_async_result(mock_get_page, None) mock_get_tokens.return_value = asyncio.Future() mock_get_tokens.return_value.set_result(["foo", "abcdef1234567890"]) mock_get_terms.return_value = [ {"code": "201904", "description": "Fall 2019 Quarter"} ] mock_get_subjects_json = utils.set_async_result( mock_get_subjects_json, data.subjects_json ) mock_upload_to_bucket().return_value = None payload = await main.run() mock_initialize.assert_called mock_get_page.assert_called mock_get_tokens.assert_called mock_get_terms.assert_called mock_get_subjects_json.assert_called mock_upload_to_bucket.assert_called assert payload[0][0]["crn"] == 10883 # error on get_subects in main where it makes a request

33.825623

86

0.745713

1,182

9,505

5.650592

0.093909

0.040874

0.067375

0.046414

0.92424

0.902081

0.894146

0.87019

0

0.036886

0.147186

9,505

280

87

33.946429

0.787071

0.005576

0

0.768182

0

0.171958

0.06

0

0.109091

1

0.036364

false

0

0.090909

0

0.127273

0

null

0

1

0

1

0

null

0

7

0cd9cdcc395fffd1692882cee87701ebbce8d789

27,564

py

Python

zauberer_game/zauber_pak/act1.py

fwalterjames/zauberer

3bc4ad4401f27900e009d4d20efaa3a438fe8017

[ "MIT" ]

null

zauberer_game/zauber_pak/act1.py

fwalterjames/zauberer

3bc4ad4401f27900e009d4d20efaa3a438fe8017

[ "MIT" ]

null

zauberer_game/zauber_pak/act1.py

fwalterjames/zauberer

3bc4ad4401f27900e009d4d20efaa3a438fe8017

[ "MIT" ]

null

from random import randint from pygame import mixer def act_one(): print("\n ========= ==== === === ======= ========= ======== ========= ======== ") print(" ==== == == === === == == == == == == == == ") print(" === === === === === ====== ======== == ==== ======== == ==== ") print(" === =========== === === == === == == == == == == ") print(" === === === === === == === == == === == == ===") print("========= === === ======== ====== ========== == == ========== == ===") print("\n💤You are dreaming, and in this dream you are many other people. You like how this feels.💤") print("\n💤 You are awakened by a harsh bang.\n") print("You are now yourself. The bang from within your bedroom.\n") input("Press enter to turn on your bedside lantern. 💡") print("\n------------💡------------") print("Your bedroom is now alight 🔥, and nothing looks out of the ordinary.\n") print("Your eyes drift to the window above your book shelf. Your brain finally registers a harsh storm out there. 🌩️ \n") night = input( "⏺️ Type SEARCH to get out of bed and look out the window, and SNOOZE to remain in bed.") if night == "SNOOZE" or night == "Snooze" or night == "snooze": print("😞 You really-really-really do not want to go over there.\n") print("You're NOT afraid, you just...you know, you're tired or whatever.\n") print("The wind howls ever madly as you attempt to drift off.\n") print("You dream of a man with skin made of iron, and of a stranger banging on your front door ⚰️") print("===============================================================\n") print("Nope! you think. Heart hammering a beat of anxiety in your chest, you climb back into bed.\n") print("The banging persists, the urgnt knocking of someone who might keep at it all night and yet who cannot take a hint.\n") print("Despite this intrusion, you drift off to sleep with relative ease, tired from the months of training and harvest you've had.\n") print("Your heart is warm with your hopes for a relaxing summer vacation... your mind is nagging with a distant worry..... ✨ ") print("--------------------------------------------- ✨ \n") input("Press enter to wake up ☀️ \n") print("Cockledoodle doo, you think, as you stretch your arms and yawn, wipe the sleep from your eyes, wishing for a few more hours abed. \n") print("You don't love farming, but your mother loved it, so you stick by it to honor her💘\n") input("Press enter to go outside and feed the chickens. 🐔🐔🐔🐔🐔 \n") print("You enter the living room, and pad over to the cottage's front door. You grab the door handle.\n") input("Press enter to open the front door.... 🚪\n") print("You gasp in surprise and take a step back.") print("Your farm looks the same as it ever did--a bit soggy from the storm, and a bit rundown from your being a lousy farmer, but nothing to gasp about.") print("No, your gasp is from the man who stands before you. 👤 A stranger...at your door...") print("The man throws up his hands. 💬 FINALLY, he says. DO YOU SLEEP WITH COTTON IN YOUR EARS?\n") print("The man is disheveled, and clearly not from this village. He wears a tattered cloak, has misshapen eyes and a wiry mustache. 👤\n") print("And he gives you the distinct impression that your life is about to change... 🥺\n") return segue() else: print("You take a deep breath, swing your legs off the bed...😶‍🌫️\n") input("Press enter to walk over and peer out the window. 🛌 ") print(" ============================") print(" == 🌧️ == /- ==") print(" == 🌧️ == \/ | ==") print(" ============================") print(" == == \ | ==") print(" == == | ==") print(" == == \ ==") print(" ============================") print("You see that a crooked branch has fallen from the apple tree on your cottage-farmhouse lawn. 🌳 \n") print("It now leans against the window's glass. 💭 This must've been the crashing that roused me, you think.") input("\nCase Closed! (Press enter to go back to bed, satisfied by your successful investigation.) 😇") print("==================❌😩=====================") leere = mixer.Sound("leere.mp3") leere.play() print("\nYou start back toward the bed 🛌\n") print("❌BANG ❌ BANG ❌BANG ❌ BANG ❌BANG ❌ \n") print("😮💭 What the hecking eff! you think, your heart racing a whole new notch.\n") print("⚠️ This new sound has come from the living room.") print("By the deep, shadow-gray of the clouds above your village, it must be after midnight and far from dawn.🕛🌑\n") print("***Your choices are, go back to sleep and pretend you have heard nothing. OR: go to the living room and investiage the banging.***") print("Please note: you live alone.") print("----------------------------------------------------------") guest = input( "⏺️ Type and enter NOPE to go back to bed, or SURE to check the door. 💫") if guest == "NOPE" or guest == "nope" or guest == "Nope": print("=============================😶‍🌫️===============================\n") print( "Nope! you think. Heart hammering anxiety drums in your chest, you climb back into bed.\n") print("The banging persists at your door, the urgnt knocking of someone who might keep at it all night and yet who cannot take a hint.\n") input("Press enter to get back out of bed and walk toward the closet 😰 \n") print(" 👁️‍🗨️ You're not going out there--you already made that choice--but you're scared, and need some guidance.\n") print( "🏴 You open the closet door and look at the full-length mirror behind the door.🚪\n") print("You need to speak with the thing that lives inside your mirror 🌀 \n") input("Press enter to activate your mirror and speak to the thing 🙃\n") print("🌀 the thing materializes over your own reflection. It looks despondent.👤\n👤Yes, it sighs more than asks, as though speaking is too much effort for it.") print("💬 I need to play rock-paper-scissors, you say: If I win, I stop stressing and get some sleep. If you win, I go answer the door.") print( "👤💬 Wait......the thing says, looking confused and alarmed. What's at the door?\n") input("Press enter to shout: IRRELEVANT!") return rock_paper_scissor() else: print("=======================") print("You take a deep breath and grab the hammer you used to fix the chicken coop just hours earlier 🔨\n") print( "🕴️ You creep out into the living room, and then you creep over to the cottage's front door.") print("You don't have a peephole--these are olden times, and no one in your village has thought of those yet--so you've got to open the door.\n") input("Press enter to open the front door... 🚪\n") print("----------------------------------- 🚪\n") print("⛈️ The world is a basin of torrential rain and thunder that happens to be shaped like your village, shaped like your farm ⛈️\n") print("Standing on your cottage porch is a strange little man. 👤\n") print("The man is disheveled, and clearly not from this county. He wears a tattered cloak, has misshapen eyes and a wiry mustache. 👤\n") print("He is soaking wet.\n") print("💬 IT'S ABOUT TIME, he wails with ornery grit. IT'S ONLY THE FATE OF THE ENTIRE CONTINENT AT STAKE!") danger = input( "⏺️ Type SAFE to slam the door in this loud, rude stranger's face, or SORRY to merely blink at him, puzzled\n") if danger == "Sorry" or danger == "SORRY" or danger == "sorry": print("You look at this stranger with groggy mind, and sleepy eyes\n") print("He speaks English, but his accent is unfamiliar to you. 🗺️\n") print( "You say,😑💬 Sir, I wish to be sleeping. How may I help you, and how quickly can it be done?") print( "He leans his face close to your face. You smell ale and unwashed horses.\n") input("Press enter to lean away... 🤢 \n") print("--------------------------------------") print("The stranger says, 💬 If you wish to keep this lovely farm, along with air in your lungs, you're gonna wanna let me in. Mate. 👤\n") print("And just like that, your life changes. 🥺") return segue() else: print("You step back and grab the door...") input( "⏺️ Type and enter: A) to smile as the door slams 🙃 | B) to look apologetic as the door slams\n") print( "💬 Yeah, sorry mate, you say, and prepare to close the door on this man and the storm he rode in on\n") print("But he shoves his muddy boot in the way 😐 \n") print( "He leans his face close to your face. You smell ale and unwashed horses.\n") input("Press enter to lean away in disgust... 🤢 \n") print("The stranger says, 💬 If you wish to keep this lovely farm, along with air in your lungs, you're gonna wanna let me in. Mate. 👤\n") print("And just like that, your life changes. 🥺") return segue() def rock_paper_scissor(): t = ["Rock", "Paper", "Scissors"] Karminrot = t[randint(0, 2)] player = False print("❤️ Welcome to ROCK-PAPER-SCISSORS! A game you play with a being cursed to live for all eternity in your family mirror! ❤️\n") print("💁‍♀️If you win, you go right back to bed, following your gut about the person at your front door.💁‍♂️\n") print("👤if you lose, you ignore your own feelings--like you always do, like your mother always did--and go answer the door.👤") print("What fun!-🥰-Let's play!") while player == False: player = input("Type: Rock, Paper, or Scissors?") if player == Karminrot: print("Tie!") return rock_paper_scissor() elif player == "Rock" or player == "rock" or player == "ROCK": if Karminrot == "Paper": print("You lose!", Karminrot, "smothers", player) print("\n======== 😐 Ugh. ==========") print( "You take a deep breath and grab the hammer you used to fix the chicken coop just hours earlier 🔨\n") print( "You creep out into the living room, and then you creep over to the cottage's front door.") print("You don't have a peephole--these are olden times, and no one in your village has thought of those yet--so you've got to open the door.\n") input("Press enter to open the front door... 🚪\n") print("----------------------------------- 🚪\n") print("⛈️ The world is a basin of torrential rain and thunder that happens to be shaped like your village, shaped like your farm ⛈️\n") print("Standing on your cottage porch is a strange little man. 👤\n") print("The man is disheveled, and clearly not from this county. He wears a tattered cloak, has misshapen eyes and a wiry mustache. 👤\n") print("He is soaking wet.\n") print( "💬 IT'S ABOUT TIME, he wails with ornery grit. IT'S ONLY THE FATE OF THE ENTIRE CONTINENT AT STAKE!") danger = input( "⏺️ Type SAFE to slam the door in this loud jerk's face, or SORRY to merely blink at him, puzzled\n") if danger == "Sorry" or danger == "SORRY" or danger == "sorry": print( "You look at this stranger with groggy mind, and sleepy eyes\n") print( "He speaks English, but his accent is unfamiliar to you. 🗺️\n") print( "You say,😑💬 Sir, I wish to be sleeping. How may I help you, and how quickly can it be done?") print( "He leans his face close to your face. You smell ale and unwashed horses.\n") input("Press enter to lean away... 🤢 \n") print("--------------------------------------") print("The stranger says, 💬 If you wish to keep this lovely farm, along with air in your lungs, you're gonna wanna let me in. Mate. 👤\n") print("And just like that, your life changes. 🥺") return segue() else: input("Press enter to smile and slam the door 🙃 \n") print( "💬 Yeah, sorry mate, you say, and prepare to close the door on this man and the storm he rode in on\n") print("But he shoves his muddy boot in the way 😐 \n") print( "He leans his face close to your face. You smell ale and unwashed horses.\n") input("Press enter to lean away... 🤢 \n") print("The stranger says, 💬 If you wish to keep this lovely farm, along with air in your lungs, you're gonna wanna let me in. Mate. 👤\n") print("And just like that, your life changes. 🥺") return segue() elif Karminrot == "Rock": print("That's a tie!") return rock_paper_scissor() else: print("You win!", player, "destroys", Karminrot) print( "\nYou sigh with relief, and you shut the closet door. You crawl into bed.") print("Despite this stress, you drift off to sleep with relative ease, tired from the months of training and harvest you've had.\n") print("Your heart is warm with your hopes for a relaxing summer vacation... your mind is nagging with a distant worry..... ✨ ") print("--------------------------------------------- ✨ \n") input("Press enter to wake up ☀️ \n") print("Cockledoodle doo, you think, as you stretch your arms and yawn, wipe the sleep from your eyes, wishing for a few more hours abed. \n") print( "You don't love farming, but your mother loved it, so you stick with it to honor her💘\n") input("Press enter to go outside and feed the chickens. 🐔🐔🐔🐔🐔 \n") print( "You enter the living room, and pad over to the cottage's front door. You grab the door handle.\n") input("Press enter to open the front door.... 🚪\n") print("You gasp in surprise and take a step back.") print("Your farm looks the same as it ever did--a bit soggy from the storm, and a bit rundown from your lack of care, but nothing to gasp about.") print("No, your gasp is from the man who stands before you. 👤") print( "The man throws up his hands. 💬 FINALLY, he says. DO YOU SLEEP WITH COTTON IN YOUR EARS?\n") print("The man is disheveled, and clearly not from this village. He wears a tattered cloak, has misshapen eyes and a wiry mustache. 👤\n") print( "And he gives you the distinct impression that your life is about to change... 🥺\n") return segue() elif player == "Paper" or player == "paper" or player == "PAPER": if Karminrot == "Scissors": print("You lose!", Karminrot, "sliced", player) print("\n======== 😐 Ugh. ==========") print( "You take a deep breath and grab the hammer you used to fix the chicken coop just hours earlier 🔨\n") print( "You creep out into the living room, and then you creep over to the cottage's front door.") print("You don't have a peephole--these are olden times, and no one in your village has thought of those yet--so you've got to open the door.\n") input("Press enter to open the front door... 🚪\n") print("----------------------------------- 🚪\n") print("⛈️ The world is a basin of torrential rain and thunder that happens to be shaped like your village, shaped like your farm ⛈️\n") print("Standing on your cottage porch is a strange little man. 👤\n") print("The man is disheveled, and clearly not from this county. He wears a tattered cloak, has misshapen eyes and a wiry mustache. 👤\n") print("He is soaking wet.\n") print( "💬 IT'S ABOUT TIME, he wails with ornery grit. IT'S ONLY THE FATE OF THE ENTIRE CONTINENT AT STAKE!") danger = input( "⏺️ Type SAFE to slam the door in this loud jerk's face, or SORRY to merely blink at him, puzzled\n") if danger == "Sorry" or danger == "SORRY" or danger == "sorry": print( "You look at this stranger with groggy mind, and sleepy eyes\n") print( "He speaks English, but his accent is unfamiliar to you. 🗺️\n") print( "You say,😑💬 Sir, I wish to be sleeping. How may I help you, and how quickly can it be done?") print( "He leans his face close to your face. You smell ale and unwashed horses.\n") input("Press enter to lean away... 🤢 \n") print("--------------------------------------") print("The stranger says, 💬 If you wish to keep this lovely farm, along with air in your lungs, you're gonna wanna let me in. Mate. 👤\n") print("And just like that, your life changes. 🥺") return segue() else: input("Press enter to smile and slam the door 🙃 \n") print( "💬 Yeah, sorry mate, you say, and prepare to close the door on this man and the storm he rode in on\n") print("But he shoves his muddy boot in the way 😐 \n") print( "He leans his face close to your face. You smell ale and unwashed horses.\n") input("Press enter to lean away... 🤢 \n") print("The stranger says, 💬 If you wish to keep this lovely farm, along with air in your lungs, you're gonna wanna let me in. Mate. 👤\n") print("And just like that, your life changes. 🥺") return segue() elif Karminrot == "Paper": print("That's a tie!") return rock_paper_scissor() else: print("You win!", player, "smothers", Karminrot) print( "\nYou sigh with relief, and you shut the closet door. You crawl into bed.") print("Despite this stress, you drift off to sleep with relative ease, tired from the months of training and harvest you've had.\n") print("Your heart is warm with your hopes for a relaxing summer vacation... your mind is nagging with a distant worry..... ✨ ") print("--------------------------------------------- ✨ \n") input("Press enter to wake up ☀️ \n") print("Cockledoodle doo, you think, as you stretch your arms and yawn, wipe the sleep from your eyes, wishing for a few more hours abed. \n") print( "You don't love farming, but your mother loved it, so you stick with it to honor her💘\n") input("Press enter to go outside and feed the chickens. 🐔🐔🐔🐔🐔 \n") print( "You enter the living room, and pad over to the cottage's front door. You grab the door handle.\n") input("Press enter to open the front door.... 🚪\n") print("You gasp in surprise and take a step back.") print("Your farm looks the same as it ever did--a bit soggy from the storm, and a bit rundown from your lack of care, but nothing to gasp about.") print("No, your gasp is from the man who stands before you. 👤") print( "The man throws up his hands. 💬 FINALLY, he says. DO YOU SLEEP WITH COTTON IN YOUR EARS?\n") print("The man is disheveled, and clearly not from this village. He wears a tattered cloak, has misshapen eyes and a wiry mustache. 👤\n") print( "And he gives you the distinct impression that your life is about to change... 🥺\n") return segue() elif player == "Scissors" or player == "scissors" or player == "SCISSORS": if Karminrot == "Rock": print("You lose...", Karminrot, "bashes", player) print("\n======== 😐 Ugh. ==========") print( "You take a deep breath and grab the hammer you used to fix the chicken coop just hours earlier 🔨\n") print( "You creep out into the living room, and then you creep over to the cottage's front door.") print("You don't have a peephole--these are olden times, and no one in your village has thought of those yet--so you've got to open the door.\n") input("Press enter to open the front door... 🚪\n") print("----------------------------------- 🚪\n") print("⛈️ The world is a basin of torrential rain and thunder that happens to be shaped like your village, shaped like your farm ⛈️\n") print("Standing on your cottage porch is a strange little man. 👤\n") print("The man is disheveled, and clearly not from this county. He wears a tattered cloak, has misshapen eyes and a wiry mustache. 👤\n") print("He is soaking wet.\n") print( "💬 IT'S ABOUT TIME, he wails with ornery grit. IT'S ONLY THE FATE OF THE ENTIRE CONTINENT AT STAKE!") danger = input( "⏺️ Type SAFE to slam the door in this loud jerk's face, or SORRY to merely blink at him, puzzled\n") if danger == "Sorry" or danger == "SORRY" or danger == "sorry": print( "You look at this stranger with groggy mind, and sleepy eyes\n") print( "He speaks English, but his accent is unfamiliar to you. 🗺️\n") print( "You say,😑💬 Sir, I wish to be sleeping. How may I help you, and how quickly can it be done?") print( "He leans his face close to your face. You smell ale and unwashed horses.\n") input("Press enter to lean away... 🤢 \n") print("--------------------------------------") print("The stranger says, 💬 If you wish to keep this lovely farm, along with air in your lungs, you're gonna wanna let me in. Mate. 👤\n") print("And just like that, your life changes. 🥺") return segue() else: input("Press enter to smile and slam the door 🙃 \n") print( "💬 Yeah, sorry mate, you say, and prepare to close the door on this man and the storm he rode in on\n") print("But he shoves his muddy boot in the way 😐 \n") print( "He leans his face close to your face. You smell ale and unwashed horses.\n") input("Press enter to lean away... 🤢 \n") print("The stranger says, 💬 If you wish to keep this lovely farm, along with air in your lungs, you're gonna wanna let me in. Mate. 👤\n") print("And just like that, your life changes. 🥺") return segue() elif Karminrot == "Scissors": print("That's a tie!") return rock_paper_scissor() else: print("You win!", player, "diced", Karminrot) print( "\nYou sigh with relief, and you shut the closet door. You crawl into bed.") print("Despite this stress, you drift off to sleep with relative ease, tired from the months of training and harvest you've had.\n") print("Your heart is warm with your hopes for a relaxing summer vacation... your mind is nagging with a distant worry..... ✨ ") print("--------------------------------------------- ✨ \n") input("Press enter to wake up ☀️ \n") print("Cockledoodle doo, you think, as you stretch your arms and yawn, wipe the sleep from your eyes, wishing for a few more hours abed. \n") print( "You don't love farming, but your mother loved it, so you stick with it to honor her💘\n") input("Press enter to go outside and feed the chickens. 🐔🐔🐔🐔🐔 \n") print( "You enter the living room, and pad over to the cottage's front door. You grab the door handle.\n") input("Press enter to open the front door.... 🚪\n") print("You gasp in surprise and take a step back.") print("Your farm looks the same as it ever did--a bit soggy from the storm, and a bit rundown from your lack of care, but nothing to gasp about.") print("No, your gasp is from the man who stands before you. 👤") print( "The man throws up his hands. 💬 FINALLY, he says. DO YOU SLEEP WITH COTTON IN YOUR EARS?\n") print("The man is disheveled, and clearly not from this village. He wears a tattered cloak, has misshapen eyes and a wiry mustache. 👤\n") print( "And he gives you the distinct impression that your life is about to change... 🥺\n") return segue() else: print( "\n 👤 I don't understand that gesture. Check your spelling maybe? Let's go again...\n") # player was set to True, but we want it to be False so the loop continues player = False Karminrot = t[randint(0, 2)] def segue(): print("✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨")

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0.026701

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0.800148

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0.758883

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false

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0b295e215286c5499ba92e826f69979c2b5e0a95

5,081

py

Python

turtlebot3_ws/src/global_path_planning/scripts/algorithms/neighbors.py

SakshayMahna/Robotics-Playground

2ad1d16b40126dde14b92d26beaa3cdb53a1b4d8

[ "MIT" ]

2

2022-03-09T07:19:04.000Z

2022-03-30T07:32:48.000Z

turtlebot3_ws/src/global_path_planning/scripts/algorithms/neighbors.py

SakshayMahna/Robotics-Playground

2ad1d16b40126dde14b92d26beaa3cdb53a1b4d8

[ "MIT" ]

1

2022-03-09T03:00:51.000Z

2022-03-12T02:53:09.000Z

turtlebot3_ws/src/global_path_planning/scripts/algorithms/neighbors.py

SakshayMahna/Robotics-Playground

2ad1d16b40126dde14b92d26beaa3cdb53a1b4d8

[ "MIT" ]

null

def find_neighbors(index, width, height, costmap, orthogonal_step_cost): """ Identifies neighbor nodes inspecting the 8 adjacent neighbors Checks if neighbor is inside the map boundaries and if is not an obstacle according to a threshold Returns a list with valid neighbour nodes as [index, step_cost] pairs """ neighbors = [] # length of diagonal = length of one side by the square root of 2 (1.41421) diagonal_step_cost = orthogonal_step_cost * 1.41421 # threshold value used to reject neighbor nodes as they are considered as obstacles [1-254] lethal_cost = 150 upper = index - width if upper > 0: if costmap[upper] < lethal_cost: step_cost = orthogonal_step_cost + costmap[upper]/255 neighbors.append([upper, step_cost]) left = index - 1 if left % width > 0: if costmap[left] < lethal_cost: step_cost = orthogonal_step_cost + costmap[left]/255 neighbors.append([left, step_cost]) upper_left = index - width - 1 if upper_left > 0 and upper_left % width > 0: if costmap[upper_left] < lethal_cost: step_cost = diagonal_step_cost + costmap[upper_left]/255 neighbors.append([index - width - 1, step_cost]) upper_right = index - width + 1 if upper_right > 0 and (upper_right) % width != (width - 1): if costmap[upper_right] < lethal_cost: step_cost = diagonal_step_cost + costmap[upper_right]/255 neighbors.append([upper_right, step_cost]) right = index + 1 if right % width != (width + 1): if costmap[right] < lethal_cost: step_cost = orthogonal_step_cost + costmap[right]/255 neighbors.append([right, step_cost]) lower_left = index + width - 1 if lower_left < height * width and lower_left % width != 0: if costmap[lower_left] < lethal_cost: step_cost = diagonal_step_cost + costmap[lower_left]/255 neighbors.append([lower_left, step_cost]) lower = index + width if lower <= height * width: if costmap[lower] < lethal_cost: step_cost = orthogonal_step_cost + costmap[lower]/255 neighbors.append([lower, step_cost]) lower_right = index + width + 1 if (lower_right) <= height * width and lower_right % width != (width - 1): if costmap[lower_right] < lethal_cost: step_cost = diagonal_step_cost + costmap[lower_right]/255 neighbors.append([lower_right, step_cost]) return neighbors def find_weighted_neighbors(index, width, height, costmap, orthogonal_step_cost): """ Identifies neighbor nodes inspecting the 8 adjacent neighbors Checks if neighbor is inside the map boundaries and if is not an obstacle according to a threshold Returns a list with valid neighbour nodes as [index, step_cost] pairs """ neighbors = [] # length of diagonal = length of one side by the square root of 2 (1.41421) diagonal_step_cost = orthogonal_step_cost * 1.41421 # threshold value used to reject neighbor nodes as they are considered as obstacles [1-254] lethal_cost = 150 step_cost = 0 upper = index - width if upper > 0: if costmap[upper] < lethal_cost: step_cost = orthogonal_step_cost + costmap[upper]/255 else: step_cost = float('inf') neighbors.append([upper, step_cost]) left = index - 1 if left % width > 0: if costmap[left] < lethal_cost: step_cost = orthogonal_step_cost + costmap[left]/255 else: step_cost = float('inf') neighbors.append([left, step_cost]) upper_left = index - width - 1 if upper_left > 0 and upper_left % width > 0: if costmap[upper_left] < lethal_cost: step_cost = diagonal_step_cost + costmap[upper_left]/255 else: step_cost = float('inf') neighbors.append([index - width - 1, step_cost]) upper_right = index - width + 1 if upper_right > 0 and (upper_right) % width != (width - 1): if costmap[upper_right] < lethal_cost: step_cost = diagonal_step_cost + costmap[upper_right]/255 else: step_cost = float('inf') neighbors.append([upper_right, step_cost]) right = index + 1 if right % width != (width + 1): if costmap[right] < lethal_cost: step_cost = orthogonal_step_cost + costmap[right]/255 else: step_cost = float('inf') neighbors.append([right, step_cost]) lower_left = index + width - 1 if lower_left < height * width and lower_left % width != 0: if costmap[lower_left] < lethal_cost: step_cost = diagonal_step_cost + costmap[lower_left]/255 else: step_cost = float('inf') neighbors.append([lower_left, step_cost]) lower = index + width if lower <= height * width: if costmap[lower] < lethal_cost: step_cost = orthogonal_step_cost + costmap[lower]/255 else: step_cost = float('inf') neighbors.append([lower, step_cost]) lower_right = index + width + 1 if (lower_right) <= height * width and lower_right % width != (width - 1): if costmap[lower_right] < lethal_cost: step_cost = diagonal_step_cost + costmap[lower_right]/255 else: step_cost = float('inf') neighbors.append([lower_right, step_cost]) return neighbors

36.292857

100

0.688644

718

5,081

4.658774

0.098886

0.155456

0.066966

0.086099

0.990732

0.968012

0.9142

0

0.030812

0.214328

5,081

140

101

36.292857

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0.155481

0

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0

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false

0

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0

null

0

1

0

1

0

null

0

7

e7f0e5b24648094826b58a90ae11185e42caa554

135

py

Python

puma/registration/__init__.py

okryush/puma

fd3f21c5566ae64110420a26ef6c9d8da0e67dce

[ "MIT" ]

239

2021-03-30T07:33:37.000Z

2022-03-15T07:14:06.000Z

puma/registration/__init__.py

alualu628628/puma

4a5980fcd302fc794f50e782e478a3bdd77f57b2

[ "MIT" ]

12

2021-06-10T17:26:36.000Z

2022-03-29T16:23:52.000Z

puma/registration/__init__.py

alualu628628/puma

4a5980fcd302fc794f50e782e478a3bdd77f57b2

[ "MIT" ]

46

2021-03-30T07:18:52.000Z

2022-03-30T04:49:34.000Z

from .method_selector import * from .o3d_aliases import * from .run_icp import * from .scan2mesh import * from .scan2mesh_icp import *

22.5

30

0.777778

19

135

5.315789

0.473684

0.39604

0.376238

0

0.026087

0.148148

135

5

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27

0.852174

0

1

0

true

0

1

0

1

0

1

0

null

1

0

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0

null

0

1

0

1

0

1

0

7

e7f9c742c2753a0b8b846e8699a107dc0f452dd0

548

py

Python

Exercicios/mundo3-exercicios-72/ex109/moeda.py

rafaelbarretomg/Curso-Python-3

7e772cbaf4c1e1bf7f1a9fb2925ec2e0eecf2998

[ "MIT" ]

null

Exercicios/mundo3-exercicios-72/ex109/moeda.py

rafaelbarretomg/Curso-Python-3

7e772cbaf4c1e1bf7f1a9fb2925ec2e0eecf2998

[ "MIT" ]

null

Exercicios/mundo3-exercicios-72/ex109/moeda.py

rafaelbarretomg/Curso-Python-3

7e772cbaf4c1e1bf7f1a9fb2925ec2e0eecf2998

[ "MIT" ]

null

def aumentar(preco=0, taxa=0, formato=False): res = preco + (preco * taxa/100) return res if formato is False else moeda(res) def diminuir(preco=0, taxa=0, formato=False): res = preco - (preco * taxa/100) return res if formato is False else moeda(res) def dobro(preco=0, formato=False): res = preco * 2 return res if not formato else moeda(res) def metade(preco=0, formato=False): res = preco / 2 return res if not formato else moeda(res) def moeda(p=0, m='R$'): return f'{m}{p:>.2f}' .replace('.', ',')

23.826087

50

0.636861

90

548

3.877778

0.277778

0.068768

0.148997

0.183381

0.836676

0

0.037296

0.217153

548

22

51

24.909091

0.776224

0

0.285714

0

0.027372

0

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0.357143

false

0

0.071429

0.714286

0

null

0

1

0

null

0

1

0

8

f025fbf9d9a45ece984ba4a2ef3b4052f7154917

124

py

Python

tkge/data/__init__.py

tkg-framework/TKG-framework

98586b7199bda0e96d74b2ea02c62226901822cc

[ "MIT", "Unlicense" ]

null

tkge/data/__init__.py

tkg-framework/TKG-framework

98586b7199bda0e96d74b2ea02c62226901822cc

[ "MIT", "Unlicense" ]

null

tkge/data/__init__.py

tkg-framework/TKG-framework

98586b7199bda0e96d74b2ea02c62226901822cc

[ "MIT", "Unlicense" ]

null

from .dataset import DatasetProcessor from .custom_dataset import ICEWS14AtiseDatasetProcessor, TestICEWS14DatasetProcessor

41.333333

85

0.903226

10

124

11.1

0.7

0.234234

0

0.034783

0.072581

124

2

86

62

0.930435

0

1

0

true

0

1

0

1

0

1

0

1

null

1

0

1

0

null

0

1

0

1

0

1

0

7

f038db53ebef4880edcef75b812d2c0c06cde9d7

1,322

py

Python

lib/operators.py

briandeheus/nots

43d1427b95fafe09417ad84b4ef2419b8e47d31c

[ "MIT" ]

4

2021-07-17T11:50:53.000Z

2022-02-10T16:43:33.000Z

lib/operators.py

briandeheus/nots

43d1427b95fafe09417ad84b4ef2419b8e47d31c

[ "MIT" ]

1

2021-07-15T17:27:32.000Z

lib/operators.py

briandeheus/nots

43d1427b95fafe09417ad84b4ef2419b8e47d31c

[ "MIT" ]

null

from lib.types import CASTING_TABLE def eq(column, value): column_type = column.type.__visit_name__ if column_type in CASTING_TABLE: return column == CASTING_TABLE[column_type].cast_to(value) return column == value def neq(column, value): column_type = column.type.__visit_name__ if column_type in CASTING_TABLE: return column != CASTING_TABLE[column_type].cast_to(value) return column != value def gte(column, value): column_type = column.type.__visit_name__ if column_type in CASTING_TABLE: return column >= CASTING_TABLE[column_type].cast_to(value) return column >= value def gt(column, value): column_type = column.type.__visit_name__ if column_type in CASTING_TABLE: return column > CASTING_TABLE[column_type].cast_to(value) return column > value def lte(column, value): column_type = column.type.__visit_name__ if column_type in CASTING_TABLE: return column <= CASTING_TABLE[column_type].cast_to(value) return column <= value def lt(column, value): column_type = column.type.__visit_name__ if column_type in CASTING_TABLE: return column < CASTING_TABLE[column_type].cast_to(value) return column < value OPERATORS = {"eq": eq, "neq": neq, "gte": gte, "gt": gt, "lt": lt}

22.40678

66

0.704236

185

1,322

4.67027

0.12973

0.277778

0.118056

0.145833

0.90625

0

0.204236

1,322

58

67

22.793103

0.821293

0

0.375

0

0.009077

0

1

0.1875

false

0

0.03125

0

0.59375

0

null

1

0

1

0

null

0

1

0

8

f0418e930ba72827ab51a284cc20ed7c3ef2f8b4

137,085

py

Python

sdk/python/pulumi_okta/app/saml.py

pulumi/pulumi-okta

83f7617a85b3d05213901773fa4e6a151ab6076b

[ "ECL-2.0", "Apache-2.0" ]

5

2019-10-29T21:59:22.000Z

2021-11-08T12:00:24.000Z

sdk/python/pulumi_okta/app/saml.py

pulumi/pulumi-okta

83f7617a85b3d05213901773fa4e6a151ab6076b

[ "ECL-2.0", "Apache-2.0" ]

109

2020-01-06T10:28:09.000Z

2022-03-25T19:52:40.000Z

sdk/python/pulumi_okta/app/saml.py

pulumi/pulumi-okta

83f7617a85b3d05213901773fa4e6a151ab6076b

[ "ECL-2.0", "Apache-2.0" ]

2

2020-09-11T16:31:04.000Z

2020-11-24T12:23:17.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs from ._inputs import * __all__ = ['SamlArgs', 'Saml'] @pulumi.input_type class SamlArgs: def __init__(__self__, *, label: pulumi.Input[str], accessibility_error_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_login_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_self_service: Optional[pulumi.Input[bool]] = None, acs_endpoints: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, admin_note: Optional[pulumi.Input[str]] = None, app_links_json: Optional[pulumi.Input[str]] = None, app_settings_json: Optional[pulumi.Input[str]] = None, assertion_signed: Optional[pulumi.Input[bool]] = None, attribute_statements: Optional[pulumi.Input[Sequence[pulumi.Input['SamlAttributeStatementArgs']]]] = None, audience: Optional[pulumi.Input[str]] = None, authn_context_class_ref: Optional[pulumi.Input[str]] = None, auto_submit_toolbar: Optional[pulumi.Input[bool]] = None, default_relay_state: Optional[pulumi.Input[str]] = None, destination: Optional[pulumi.Input[str]] = None, digest_algorithm: Optional[pulumi.Input[str]] = None, enduser_note: Optional[pulumi.Input[str]] = None, features: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, hide_ios: Optional[pulumi.Input[bool]] = None, hide_web: Optional[pulumi.Input[bool]] = None, honor_force_authn: Optional[pulumi.Input[bool]] = None, idp_issuer: Optional[pulumi.Input[str]] = None, inline_hook_id: Optional[pulumi.Input[str]] = None, key_name: Optional[pulumi.Input[str]] = None, key_years_valid: Optional[pulumi.Input[int]] = None, logo: Optional[pulumi.Input[str]] = None, preconfigured_app: Optional[pulumi.Input[str]] = None, recipient: Optional[pulumi.Input[str]] = None, request_compressed: Optional[pulumi.Input[bool]] = None, response_signed: Optional[pulumi.Input[bool]] = None, saml_version: Optional[pulumi.Input[str]] = None, signature_algorithm: Optional[pulumi.Input[str]] = None, single_logout_certificate: Optional[pulumi.Input[str]] = None, single_logout_issuer: Optional[pulumi.Input[str]] = None, single_logout_url: Optional[pulumi.Input[str]] = None, skip_groups: Optional[pulumi.Input[bool]] = None, skip_users: Optional[pulumi.Input[bool]] = None, sp_issuer: Optional[pulumi.Input[str]] = None, sso_url: Optional[pulumi.Input[str]] = None, status: Optional[pulumi.Input[str]] = None, subject_name_id_format: Optional[pulumi.Input[str]] = None, subject_name_id_template: Optional[pulumi.Input[str]] = None, user_name_template: Optional[pulumi.Input[str]] = None, user_name_template_suffix: Optional[pulumi.Input[str]] = None, user_name_template_type: Optional[pulumi.Input[str]] = None, users: Optional[pulumi.Input[Sequence[pulumi.Input['SamlUserArgs']]]] = None): """ The set of arguments for constructing a Saml resource. :param pulumi.Input[str] label: label of application. :param pulumi.Input[str] accessibility_error_redirect_url: Custom error page URL. :param pulumi.Input[str] accessibility_login_redirect_url: Custom login page for this application. :param pulumi.Input[bool] accessibility_self_service: Enable self-service. By default, it is `false`. :param pulumi.Input[Sequence[pulumi.Input[str]]] acs_endpoints: An array of ACS endpoints. You can configure a maximum of 100 endpoints. :param pulumi.Input[str] admin_note: Application notes for admins. :param pulumi.Input[str] app_links_json: Displays specific appLinks for the app. The value for the link should be boolean. :param pulumi.Input[str] app_settings_json: Application settings in JSON format. :param pulumi.Input[bool] assertion_signed: Determines whether the SAML assertion is digitally signed. :param pulumi.Input[Sequence[pulumi.Input['SamlAttributeStatementArgs']]] attribute_statements: List of SAML Attribute statements. :param pulumi.Input[str] audience: Audience restriction. :param pulumi.Input[str] authn_context_class_ref: Identifies the SAML authentication context class for the assertion’s authentication statement. :param pulumi.Input[bool] auto_submit_toolbar: Display auto submit toolbar. :param pulumi.Input[str] default_relay_state: Identifies a specific application resource in an IDP initiated SSO scenario. :param pulumi.Input[str] destination: Identifies the location where the SAML response is intended to be sent inside the SAML assertion. :param pulumi.Input[str] digest_algorithm: Determines the digest algorithm used to digitally sign the SAML assertion and response. :param pulumi.Input[str] enduser_note: Application notes for end users. :param pulumi.Input[Sequence[pulumi.Input[str]]] features: features enabled. Notice: you can't currently configure provisioning features via the API. :param pulumi.Input[Sequence[pulumi.Input[str]]] groups: Groups associated with the application. - `DEPRECATED`: Please replace usage with the `AppGroupAssignments` (or `app.GroupAssignment`) resource. :param pulumi.Input[bool] hide_ios: Do not display application icon on mobile app. :param pulumi.Input[bool] hide_web: Do not display application icon to users :param pulumi.Input[bool] honor_force_authn: Prompt user to re-authenticate if SP asks for it. :param pulumi.Input[str] idp_issuer: SAML issuer ID. :param pulumi.Input[str] inline_hook_id: Saml Inline Hook associated with the application. :param pulumi.Input[str] key_name: Certificate name. This modulates the rotation of keys. New name == new key. Required to be set with `key_years_valid`. :param pulumi.Input[int] key_years_valid: Number of years the certificate is valid (2 - 10 years). :param pulumi.Input[str] logo: Local file path to the logo. The file must be in PNG, JPG, or GIF format, and less than 1 MB in size. :param pulumi.Input[str] preconfigured_app: name of application from the Okta Integration Network, if not included a custom app will be created. :param pulumi.Input[str] recipient: The location where the app may present the SAML assertion. :param pulumi.Input[bool] request_compressed: Denotes whether the request is compressed or not. :param pulumi.Input[bool] response_signed: Determines whether the SAML auth response message is digitally signed. :param pulumi.Input[str] saml_version: SAML version for the app's sign-on mode. Valid values are: `"2.0"` or `"1.1"`. Default is `"2.0"`. :param pulumi.Input[str] signature_algorithm: Signature algorithm used ot digitally sign the assertion and response. :param pulumi.Input[str] single_logout_certificate: x509 encoded certificate that the Service Provider uses to sign Single Logout requests. Note: should be provided without `-----BEGIN CERTIFICATE-----` and `-----END CERTIFICATE-----`, see [official documentation](https://developer.okta.com/docs/reference/api/apps/#service-provider-certificate). :param pulumi.Input[str] single_logout_issuer: The issuer of the Service Provider that generates the Single Logout request. :param pulumi.Input[str] single_logout_url: The location where the logout response is sent. :param pulumi.Input[bool] skip_groups: Indicator that allows the app to skip `groups` sync (it's also can be provided during import). Default is `false`. :param pulumi.Input[bool] skip_users: Indicator that allows the app to skip `users` sync (it's also can be provided during import). Default is `false`. :param pulumi.Input[str] sp_issuer: SAML service provider issuer. :param pulumi.Input[str] sso_url: Single Sign-on Url. :param pulumi.Input[str] status: status of application. :param pulumi.Input[str] subject_name_id_format: Identifies the SAML processing rules. :param pulumi.Input[str] subject_name_id_template: Template for app user's username when a user is assigned to the app. :param pulumi.Input[str] user_name_template: Username template. :param pulumi.Input[str] user_name_template_suffix: Username template suffix. :param pulumi.Input[str] user_name_template_type: Username template type. :param pulumi.Input[Sequence[pulumi.Input['SamlUserArgs']]] users: Users associated with the application. - `DEPRECATED`: Please replace usage with the `app.User` resource. """ pulumi.set(__self__, "label", label) if accessibility_error_redirect_url is not None: pulumi.set(__self__, "accessibility_error_redirect_url", accessibility_error_redirect_url) if accessibility_login_redirect_url is not None: pulumi.set(__self__, "accessibility_login_redirect_url", accessibility_login_redirect_url) if accessibility_self_service is not None: pulumi.set(__self__, "accessibility_self_service", accessibility_self_service) if acs_endpoints is not None: pulumi.set(__self__, "acs_endpoints", acs_endpoints) if admin_note is not None: pulumi.set(__self__, "admin_note", admin_note) if app_links_json is not None: pulumi.set(__self__, "app_links_json", app_links_json) if app_settings_json is not None: pulumi.set(__self__, "app_settings_json", app_settings_json) if assertion_signed is not None: pulumi.set(__self__, "assertion_signed", assertion_signed) if attribute_statements is not None: pulumi.set(__self__, "attribute_statements", attribute_statements) if audience is not None: pulumi.set(__self__, "audience", audience) if authn_context_class_ref is not None: pulumi.set(__self__, "authn_context_class_ref", authn_context_class_ref) if auto_submit_toolbar is not None: pulumi.set(__self__, "auto_submit_toolbar", auto_submit_toolbar) if default_relay_state is not None: pulumi.set(__self__, "default_relay_state", default_relay_state) if destination is not None: pulumi.set(__self__, "destination", destination) if digest_algorithm is not None: pulumi.set(__self__, "digest_algorithm", digest_algorithm) if enduser_note is not None: pulumi.set(__self__, "enduser_note", enduser_note) if features is not None: pulumi.set(__self__, "features", features) if groups is not None: warnings.warn("""The direct configuration of groups in this app resource is deprecated, please ensure you use the resource `okta_app_group_assignments` for this functionality.""", DeprecationWarning) pulumi.log.warn("""groups is deprecated: The direct configuration of groups in this app resource is deprecated, please ensure you use the resource `okta_app_group_assignments` for this functionality.""") if groups is not None: pulumi.set(__self__, "groups", groups) if hide_ios is not None: pulumi.set(__self__, "hide_ios", hide_ios) if hide_web is not None: pulumi.set(__self__, "hide_web", hide_web) if honor_force_authn is not None: pulumi.set(__self__, "honor_force_authn", honor_force_authn) if idp_issuer is not None: pulumi.set(__self__, "idp_issuer", idp_issuer) if inline_hook_id is not None: pulumi.set(__self__, "inline_hook_id", inline_hook_id) if key_name is not None: pulumi.set(__self__, "key_name", key_name) if key_years_valid is not None: pulumi.set(__self__, "key_years_valid", key_years_valid) if logo is not None: pulumi.set(__self__, "logo", logo) if preconfigured_app is not None: pulumi.set(__self__, "preconfigured_app", preconfigured_app) if recipient is not None: pulumi.set(__self__, "recipient", recipient) if request_compressed is not None: pulumi.set(__self__, "request_compressed", request_compressed) if response_signed is not None: pulumi.set(__self__, "response_signed", response_signed) if saml_version is not None: pulumi.set(__self__, "saml_version", saml_version) if signature_algorithm is not None: pulumi.set(__self__, "signature_algorithm", signature_algorithm) if single_logout_certificate is not None: pulumi.set(__self__, "single_logout_certificate", single_logout_certificate) if single_logout_issuer is not None: pulumi.set(__self__, "single_logout_issuer", single_logout_issuer) if single_logout_url is not None: pulumi.set(__self__, "single_logout_url", single_logout_url) if skip_groups is not None: pulumi.set(__self__, "skip_groups", skip_groups) if skip_users is not None: pulumi.set(__self__, "skip_users", skip_users) if sp_issuer is not None: pulumi.set(__self__, "sp_issuer", sp_issuer) if sso_url is not None: pulumi.set(__self__, "sso_url", sso_url) if status is not None: pulumi.set(__self__, "status", status) if subject_name_id_format is not None: pulumi.set(__self__, "subject_name_id_format", subject_name_id_format) if subject_name_id_template is not None: pulumi.set(__self__, "subject_name_id_template", subject_name_id_template) if user_name_template is not None: pulumi.set(__self__, "user_name_template", user_name_template) if user_name_template_suffix is not None: pulumi.set(__self__, "user_name_template_suffix", user_name_template_suffix) if user_name_template_type is not None: pulumi.set(__self__, "user_name_template_type", user_name_template_type) if users is not None: warnings.warn("""The direct configuration of users in this app resource is deprecated, please ensure you use the resource `okta_app_user` for this functionality.""", DeprecationWarning) pulumi.log.warn("""users is deprecated: The direct configuration of users in this app resource is deprecated, please ensure you use the resource `okta_app_user` for this functionality.""") if users is not None: pulumi.set(__self__, "users", users) @property @pulumi.getter def label(self) -> pulumi.Input[str]: """ label of application. """ return pulumi.get(self, "label") @label.setter def label(self, value: pulumi.Input[str]): pulumi.set(self, "label", value) @property @pulumi.getter(name="accessibilityErrorRedirectUrl") def accessibility_error_redirect_url(self) -> Optional[pulumi.Input[str]]: """ Custom error page URL. """ return pulumi.get(self, "accessibility_error_redirect_url") @accessibility_error_redirect_url.setter def accessibility_error_redirect_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "accessibility_error_redirect_url", value) @property @pulumi.getter(name="accessibilityLoginRedirectUrl") def accessibility_login_redirect_url(self) -> Optional[pulumi.Input[str]]: """ Custom login page for this application. """ return pulumi.get(self, "accessibility_login_redirect_url") @accessibility_login_redirect_url.setter def accessibility_login_redirect_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "accessibility_login_redirect_url", value) @property @pulumi.getter(name="accessibilitySelfService") def accessibility_self_service(self) -> Optional[pulumi.Input[bool]]: """ Enable self-service. By default, it is `false`. """ return pulumi.get(self, "accessibility_self_service") @accessibility_self_service.setter def accessibility_self_service(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "accessibility_self_service", value) @property @pulumi.getter(name="acsEndpoints") def acs_endpoints(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ An array of ACS endpoints. You can configure a maximum of 100 endpoints. """ return pulumi.get(self, "acs_endpoints") @acs_endpoints.setter def acs_endpoints(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "acs_endpoints", value) @property @pulumi.getter(name="adminNote") def admin_note(self) -> Optional[pulumi.Input[str]]: """ Application notes for admins. """ return pulumi.get(self, "admin_note") @admin_note.setter def admin_note(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "admin_note", value) @property @pulumi.getter(name="appLinksJson") def app_links_json(self) -> Optional[pulumi.Input[str]]: """ Displays specific appLinks for the app. The value for the link should be boolean. """ return pulumi.get(self, "app_links_json") @app_links_json.setter def app_links_json(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "app_links_json", value) @property @pulumi.getter(name="appSettingsJson") def app_settings_json(self) -> Optional[pulumi.Input[str]]: """ Application settings in JSON format. """ return pulumi.get(self, "app_settings_json") @app_settings_json.setter def app_settings_json(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "app_settings_json", value) @property @pulumi.getter(name="assertionSigned") def assertion_signed(self) -> Optional[pulumi.Input[bool]]: """ Determines whether the SAML assertion is digitally signed. """ return pulumi.get(self, "assertion_signed") @assertion_signed.setter def assertion_signed(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "assertion_signed", value) @property @pulumi.getter(name="attributeStatements") def attribute_statements(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['SamlAttributeStatementArgs']]]]: """ List of SAML Attribute statements. """ return pulumi.get(self, "attribute_statements") @attribute_statements.setter def attribute_statements(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['SamlAttributeStatementArgs']]]]): pulumi.set(self, "attribute_statements", value) @property @pulumi.getter def audience(self) -> Optional[pulumi.Input[str]]: """ Audience restriction. """ return pulumi.get(self, "audience") @audience.setter def audience(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "audience", value) @property @pulumi.getter(name="authnContextClassRef") def authn_context_class_ref(self) -> Optional[pulumi.Input[str]]: """ Identifies the SAML authentication context class for the assertion’s authentication statement. """ return pulumi.get(self, "authn_context_class_ref") @authn_context_class_ref.setter def authn_context_class_ref(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "authn_context_class_ref", value) @property @pulumi.getter(name="autoSubmitToolbar") def auto_submit_toolbar(self) -> Optional[pulumi.Input[bool]]: """ Display auto submit toolbar. """ return pulumi.get(self, "auto_submit_toolbar") @auto_submit_toolbar.setter def auto_submit_toolbar(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "auto_submit_toolbar", value) @property @pulumi.getter(name="defaultRelayState") def default_relay_state(self) -> Optional[pulumi.Input[str]]: """ Identifies a specific application resource in an IDP initiated SSO scenario. """ return pulumi.get(self, "default_relay_state") @default_relay_state.setter def default_relay_state(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "default_relay_state", value) @property @pulumi.getter def destination(self) -> Optional[pulumi.Input[str]]: """ Identifies the location where the SAML response is intended to be sent inside the SAML assertion. """ return pulumi.get(self, "destination") @destination.setter def destination(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "destination", value) @property @pulumi.getter(name="digestAlgorithm") def digest_algorithm(self) -> Optional[pulumi.Input[str]]: """ Determines the digest algorithm used to digitally sign the SAML assertion and response. """ return pulumi.get(self, "digest_algorithm") @digest_algorithm.setter def digest_algorithm(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "digest_algorithm", value) @property @pulumi.getter(name="enduserNote") def enduser_note(self) -> Optional[pulumi.Input[str]]: """ Application notes for end users. """ return pulumi.get(self, "enduser_note") @enduser_note.setter def enduser_note(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "enduser_note", value) @property @pulumi.getter def features(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ features enabled. Notice: you can't currently configure provisioning features via the API. """ return pulumi.get(self, "features") @features.setter def features(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "features", value) @property @pulumi.getter def groups(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Groups associated with the application. - `DEPRECATED`: Please replace usage with the `AppGroupAssignments` (or `app.GroupAssignment`) resource. """ return pulumi.get(self, "groups") @groups.setter def groups(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "groups", value) @property @pulumi.getter(name="hideIos") def hide_ios(self) -> Optional[pulumi.Input[bool]]: """ Do not display application icon on mobile app. """ return pulumi.get(self, "hide_ios") @hide_ios.setter def hide_ios(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "hide_ios", value) @property @pulumi.getter(name="hideWeb") def hide_web(self) -> Optional[pulumi.Input[bool]]: """ Do not display application icon to users """ return pulumi.get(self, "hide_web") @hide_web.setter def hide_web(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "hide_web", value) @property @pulumi.getter(name="honorForceAuthn") def honor_force_authn(self) -> Optional[pulumi.Input[bool]]: """ Prompt user to re-authenticate if SP asks for it. """ return pulumi.get(self, "honor_force_authn") @honor_force_authn.setter def honor_force_authn(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "honor_force_authn", value) @property @pulumi.getter(name="idpIssuer") def idp_issuer(self) -> Optional[pulumi.Input[str]]: """ SAML issuer ID. """ return pulumi.get(self, "idp_issuer") @idp_issuer.setter def idp_issuer(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "idp_issuer", value) @property @pulumi.getter(name="inlineHookId") def inline_hook_id(self) -> Optional[pulumi.Input[str]]: """ Saml Inline Hook associated with the application. """ return pulumi.get(self, "inline_hook_id") @inline_hook_id.setter def inline_hook_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "inline_hook_id", value) @property @pulumi.getter(name="keyName") def key_name(self) -> Optional[pulumi.Input[str]]: """ Certificate name. This modulates the rotation of keys. New name == new key. Required to be set with `key_years_valid`. """ return pulumi.get(self, "key_name") @key_name.setter def key_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "key_name", value) @property @pulumi.getter(name="keyYearsValid") def key_years_valid(self) -> Optional[pulumi.Input[int]]: """ Number of years the certificate is valid (2 - 10 years). """ return pulumi.get(self, "key_years_valid") @key_years_valid.setter def key_years_valid(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "key_years_valid", value) @property @pulumi.getter def logo(self) -> Optional[pulumi.Input[str]]: """ Local file path to the logo. The file must be in PNG, JPG, or GIF format, and less than 1 MB in size. """ return pulumi.get(self, "logo") @logo.setter def logo(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "logo", value) @property @pulumi.getter(name="preconfiguredApp") def preconfigured_app(self) -> Optional[pulumi.Input[str]]: """ name of application from the Okta Integration Network, if not included a custom app will be created. """ return pulumi.get(self, "preconfigured_app") @preconfigured_app.setter def preconfigured_app(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "preconfigured_app", value) @property @pulumi.getter def recipient(self) -> Optional[pulumi.Input[str]]: """ The location where the app may present the SAML assertion. """ return pulumi.get(self, "recipient") @recipient.setter def recipient(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "recipient", value) @property @pulumi.getter(name="requestCompressed") def request_compressed(self) -> Optional[pulumi.Input[bool]]: """ Denotes whether the request is compressed or not. """ return pulumi.get(self, "request_compressed") @request_compressed.setter def request_compressed(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "request_compressed", value) @property @pulumi.getter(name="responseSigned") def response_signed(self) -> Optional[pulumi.Input[bool]]: """ Determines whether the SAML auth response message is digitally signed. """ return pulumi.get(self, "response_signed") @response_signed.setter def response_signed(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "response_signed", value) @property @pulumi.getter(name="samlVersion") def saml_version(self) -> Optional[pulumi.Input[str]]: """ SAML version for the app's sign-on mode. Valid values are: `"2.0"` or `"1.1"`. Default is `"2.0"`. """ return pulumi.get(self, "saml_version") @saml_version.setter def saml_version(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "saml_version", value) @property @pulumi.getter(name="signatureAlgorithm") def signature_algorithm(self) -> Optional[pulumi.Input[str]]: """ Signature algorithm used ot digitally sign the assertion and response. """ return pulumi.get(self, "signature_algorithm") @signature_algorithm.setter def signature_algorithm(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "signature_algorithm", value) @property @pulumi.getter(name="singleLogoutCertificate") def single_logout_certificate(self) -> Optional[pulumi.Input[str]]: """ x509 encoded certificate that the Service Provider uses to sign Single Logout requests. Note: should be provided without `-----BEGIN CERTIFICATE-----` and `-----END CERTIFICATE-----`, see [official documentation](https://developer.okta.com/docs/reference/api/apps/#service-provider-certificate). """ return pulumi.get(self, "single_logout_certificate") @single_logout_certificate.setter def single_logout_certificate(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "single_logout_certificate", value) @property @pulumi.getter(name="singleLogoutIssuer") def single_logout_issuer(self) -> Optional[pulumi.Input[str]]: """ The issuer of the Service Provider that generates the Single Logout request. """ return pulumi.get(self, "single_logout_issuer") @single_logout_issuer.setter def single_logout_issuer(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "single_logout_issuer", value) @property @pulumi.getter(name="singleLogoutUrl") def single_logout_url(self) -> Optional[pulumi.Input[str]]: """ The location where the logout response is sent. """ return pulumi.get(self, "single_logout_url") @single_logout_url.setter def single_logout_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "single_logout_url", value) @property @pulumi.getter(name="skipGroups") def skip_groups(self) -> Optional[pulumi.Input[bool]]: """ Indicator that allows the app to skip `groups` sync (it's also can be provided during import). Default is `false`. """ return pulumi.get(self, "skip_groups") @skip_groups.setter def skip_groups(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "skip_groups", value) @property @pulumi.getter(name="skipUsers") def skip_users(self) -> Optional[pulumi.Input[bool]]: """ Indicator that allows the app to skip `users` sync (it's also can be provided during import). Default is `false`. """ return pulumi.get(self, "skip_users") @skip_users.setter def skip_users(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "skip_users", value) @property @pulumi.getter(name="spIssuer") def sp_issuer(self) -> Optional[pulumi.Input[str]]: """ SAML service provider issuer. """ return pulumi.get(self, "sp_issuer") @sp_issuer.setter def sp_issuer(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "sp_issuer", value) @property @pulumi.getter(name="ssoUrl") def sso_url(self) -> Optional[pulumi.Input[str]]: """ Single Sign-on Url. """ return pulumi.get(self, "sso_url") @sso_url.setter def sso_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "sso_url", value) @property @pulumi.getter def status(self) -> Optional[pulumi.Input[str]]: """ status of application. """ return pulumi.get(self, "status") @status.setter def status(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "status", value) @property @pulumi.getter(name="subjectNameIdFormat") def subject_name_id_format(self) -> Optional[pulumi.Input[str]]: """ Identifies the SAML processing rules. """ return pulumi.get(self, "subject_name_id_format") @subject_name_id_format.setter def subject_name_id_format(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "subject_name_id_format", value) @property @pulumi.getter(name="subjectNameIdTemplate") def subject_name_id_template(self) -> Optional[pulumi.Input[str]]: """ Template for app user's username when a user is assigned to the app. """ return pulumi.get(self, "subject_name_id_template") @subject_name_id_template.setter def subject_name_id_template(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "subject_name_id_template", value) @property @pulumi.getter(name="userNameTemplate") def user_name_template(self) -> Optional[pulumi.Input[str]]: """ Username template. """ return pulumi.get(self, "user_name_template") @user_name_template.setter def user_name_template(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "user_name_template", value) @property @pulumi.getter(name="userNameTemplateSuffix") def user_name_template_suffix(self) -> Optional[pulumi.Input[str]]: """ Username template suffix. """ return pulumi.get(self, "user_name_template_suffix") @user_name_template_suffix.setter def user_name_template_suffix(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "user_name_template_suffix", value) @property @pulumi.getter(name="userNameTemplateType") def user_name_template_type(self) -> Optional[pulumi.Input[str]]: """ Username template type. """ return pulumi.get(self, "user_name_template_type") @user_name_template_type.setter def user_name_template_type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "user_name_template_type", value) @property @pulumi.getter def users(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['SamlUserArgs']]]]: """ Users associated with the application. - `DEPRECATED`: Please replace usage with the `app.User` resource. """ return pulumi.get(self, "users") @users.setter def users(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['SamlUserArgs']]]]): pulumi.set(self, "users", value) @pulumi.input_type class _SamlState: def __init__(__self__, *, accessibility_error_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_login_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_self_service: Optional[pulumi.Input[bool]] = None, acs_endpoints: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, admin_note: Optional[pulumi.Input[str]] = None, app_links_json: Optional[pulumi.Input[str]] = None, app_settings_json: Optional[pulumi.Input[str]] = None, assertion_signed: Optional[pulumi.Input[bool]] = None, attribute_statements: Optional[pulumi.Input[Sequence[pulumi.Input['SamlAttributeStatementArgs']]]] = None, audience: Optional[pulumi.Input[str]] = None, authn_context_class_ref: Optional[pulumi.Input[str]] = None, auto_submit_toolbar: Optional[pulumi.Input[bool]] = None, certificate: Optional[pulumi.Input[str]] = None, default_relay_state: Optional[pulumi.Input[str]] = None, destination: Optional[pulumi.Input[str]] = None, digest_algorithm: Optional[pulumi.Input[str]] = None, enduser_note: Optional[pulumi.Input[str]] = None, entity_key: Optional[pulumi.Input[str]] = None, entity_url: Optional[pulumi.Input[str]] = None, features: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, hide_ios: Optional[pulumi.Input[bool]] = None, hide_web: Optional[pulumi.Input[bool]] = None, honor_force_authn: Optional[pulumi.Input[bool]] = None, http_post_binding: Optional[pulumi.Input[str]] = None, http_redirect_binding: Optional[pulumi.Input[str]] = None, idp_issuer: Optional[pulumi.Input[str]] = None, inline_hook_id: Optional[pulumi.Input[str]] = None, key_id: Optional[pulumi.Input[str]] = None, key_name: Optional[pulumi.Input[str]] = None, key_years_valid: Optional[pulumi.Input[int]] = None, label: Optional[pulumi.Input[str]] = None, logo: Optional[pulumi.Input[str]] = None, logo_url: Optional[pulumi.Input[str]] = None, metadata: Optional[pulumi.Input[str]] = None, metadata_url: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, preconfigured_app: Optional[pulumi.Input[str]] = None, recipient: Optional[pulumi.Input[str]] = None, request_compressed: Optional[pulumi.Input[bool]] = None, response_signed: Optional[pulumi.Input[bool]] = None, saml_version: Optional[pulumi.Input[str]] = None, sign_on_mode: Optional[pulumi.Input[str]] = None, signature_algorithm: Optional[pulumi.Input[str]] = None, single_logout_certificate: Optional[pulumi.Input[str]] = None, single_logout_issuer: Optional[pulumi.Input[str]] = None, single_logout_url: Optional[pulumi.Input[str]] = None, skip_groups: Optional[pulumi.Input[bool]] = None, skip_users: Optional[pulumi.Input[bool]] = None, sp_issuer: Optional[pulumi.Input[str]] = None, sso_url: Optional[pulumi.Input[str]] = None, status: Optional[pulumi.Input[str]] = None, subject_name_id_format: Optional[pulumi.Input[str]] = None, subject_name_id_template: Optional[pulumi.Input[str]] = None, user_name_template: Optional[pulumi.Input[str]] = None, user_name_template_suffix: Optional[pulumi.Input[str]] = None, user_name_template_type: Optional[pulumi.Input[str]] = None, users: Optional[pulumi.Input[Sequence[pulumi.Input['SamlUserArgs']]]] = None): """ Input properties used for looking up and filtering Saml resources. :param pulumi.Input[str] accessibility_error_redirect_url: Custom error page URL. :param pulumi.Input[str] accessibility_login_redirect_url: Custom login page for this application. :param pulumi.Input[bool] accessibility_self_service: Enable self-service. By default, it is `false`. :param pulumi.Input[Sequence[pulumi.Input[str]]] acs_endpoints: An array of ACS endpoints. You can configure a maximum of 100 endpoints. :param pulumi.Input[str] admin_note: Application notes for admins. :param pulumi.Input[str] app_links_json: Displays specific appLinks for the app. The value for the link should be boolean. :param pulumi.Input[str] app_settings_json: Application settings in JSON format. :param pulumi.Input[bool] assertion_signed: Determines whether the SAML assertion is digitally signed. :param pulumi.Input[Sequence[pulumi.Input['SamlAttributeStatementArgs']]] attribute_statements: List of SAML Attribute statements. :param pulumi.Input[str] audience: Audience restriction. :param pulumi.Input[str] authn_context_class_ref: Identifies the SAML authentication context class for the assertion’s authentication statement. :param pulumi.Input[bool] auto_submit_toolbar: Display auto submit toolbar. :param pulumi.Input[str] certificate: The raw signing certificate. :param pulumi.Input[str] default_relay_state: Identifies a specific application resource in an IDP initiated SSO scenario. :param pulumi.Input[str] destination: Identifies the location where the SAML response is intended to be sent inside the SAML assertion. :param pulumi.Input[str] digest_algorithm: Determines the digest algorithm used to digitally sign the SAML assertion and response. :param pulumi.Input[str] enduser_note: Application notes for end users. :param pulumi.Input[str] entity_key: Entity ID, the ID portion of the `entity_url`. :param pulumi.Input[str] entity_url: Entity URL for instance [http://www.okta.com/exk1fcia6d6EMsf331d8](http://www.okta.com/exk1fcia6d6EMsf331d8). :param pulumi.Input[Sequence[pulumi.Input[str]]] features: features enabled. Notice: you can't currently configure provisioning features via the API. :param pulumi.Input[Sequence[pulumi.Input[str]]] groups: Groups associated with the application. - `DEPRECATED`: Please replace usage with the `AppGroupAssignments` (or `app.GroupAssignment`) resource. :param pulumi.Input[bool] hide_ios: Do not display application icon on mobile app. :param pulumi.Input[bool] hide_web: Do not display application icon to users :param pulumi.Input[bool] honor_force_authn: Prompt user to re-authenticate if SP asks for it. :param pulumi.Input[str] http_post_binding: `urn:oasis:names:tc:SAML:2.0:bindings:HTTP-Post` location from the SAML metadata. :param pulumi.Input[str] http_redirect_binding: `urn:oasis:names:tc:SAML:2.0:bindings:HTTP-Redirect` location from the SAML metadata. :param pulumi.Input[str] idp_issuer: SAML issuer ID. :param pulumi.Input[str] inline_hook_id: Saml Inline Hook associated with the application. :param pulumi.Input[str] key_id: Certificate key ID. :param pulumi.Input[str] key_name: Certificate name. This modulates the rotation of keys. New name == new key. Required to be set with `key_years_valid`. :param pulumi.Input[int] key_years_valid: Number of years the certificate is valid (2 - 10 years). :param pulumi.Input[str] label: label of application. :param pulumi.Input[str] logo: Local file path to the logo. The file must be in PNG, JPG, or GIF format, and less than 1 MB in size. :param pulumi.Input[str] logo_url: Direct link of application logo. :param pulumi.Input[str] metadata: The raw SAML metadata in XML. :param pulumi.Input[str] metadata_url: SAML xml metadata URL. :param pulumi.Input[str] name: The name of the attribute statement. :param pulumi.Input[str] preconfigured_app: name of application from the Okta Integration Network, if not included a custom app will be created. :param pulumi.Input[str] recipient: The location where the app may present the SAML assertion. :param pulumi.Input[bool] request_compressed: Denotes whether the request is compressed or not. :param pulumi.Input[bool] response_signed: Determines whether the SAML auth response message is digitally signed. :param pulumi.Input[str] saml_version: SAML version for the app's sign-on mode. Valid values are: `"2.0"` or `"1.1"`. Default is `"2.0"`. :param pulumi.Input[str] sign_on_mode: Sign-on mode of application. :param pulumi.Input[str] signature_algorithm: Signature algorithm used ot digitally sign the assertion and response. :param pulumi.Input[str] single_logout_certificate: x509 encoded certificate that the Service Provider uses to sign Single Logout requests. Note: should be provided without `-----BEGIN CERTIFICATE-----` and `-----END CERTIFICATE-----`, see [official documentation](https://developer.okta.com/docs/reference/api/apps/#service-provider-certificate). :param pulumi.Input[str] single_logout_issuer: The issuer of the Service Provider that generates the Single Logout request. :param pulumi.Input[str] single_logout_url: The location where the logout response is sent. :param pulumi.Input[bool] skip_groups: Indicator that allows the app to skip `groups` sync (it's also can be provided during import). Default is `false`. :param pulumi.Input[bool] skip_users: Indicator that allows the app to skip `users` sync (it's also can be provided during import). Default is `false`. :param pulumi.Input[str] sp_issuer: SAML service provider issuer. :param pulumi.Input[str] sso_url: Single Sign-on Url. :param pulumi.Input[str] status: status of application. :param pulumi.Input[str] subject_name_id_format: Identifies the SAML processing rules. :param pulumi.Input[str] subject_name_id_template: Template for app user's username when a user is assigned to the app. :param pulumi.Input[str] user_name_template: Username template. :param pulumi.Input[str] user_name_template_suffix: Username template suffix. :param pulumi.Input[str] user_name_template_type: Username template type. :param pulumi.Input[Sequence[pulumi.Input['SamlUserArgs']]] users: Users associated with the application. - `DEPRECATED`: Please replace usage with the `app.User` resource. """ if accessibility_error_redirect_url is not None: pulumi.set(__self__, "accessibility_error_redirect_url", accessibility_error_redirect_url) if accessibility_login_redirect_url is not None: pulumi.set(__self__, "accessibility_login_redirect_url", accessibility_login_redirect_url) if accessibility_self_service is not None: pulumi.set(__self__, "accessibility_self_service", accessibility_self_service) if acs_endpoints is not None: pulumi.set(__self__, "acs_endpoints", acs_endpoints) if admin_note is not None: pulumi.set(__self__, "admin_note", admin_note) if app_links_json is not None: pulumi.set(__self__, "app_links_json", app_links_json) if app_settings_json is not None: pulumi.set(__self__, "app_settings_json", app_settings_json) if assertion_signed is not None: pulumi.set(__self__, "assertion_signed", assertion_signed) if attribute_statements is not None: pulumi.set(__self__, "attribute_statements", attribute_statements) if audience is not None: pulumi.set(__self__, "audience", audience) if authn_context_class_ref is not None: pulumi.set(__self__, "authn_context_class_ref", authn_context_class_ref) if auto_submit_toolbar is not None: pulumi.set(__self__, "auto_submit_toolbar", auto_submit_toolbar) if certificate is not None: pulumi.set(__self__, "certificate", certificate) if default_relay_state is not None: pulumi.set(__self__, "default_relay_state", default_relay_state) if destination is not None: pulumi.set(__self__, "destination", destination) if digest_algorithm is not None: pulumi.set(__self__, "digest_algorithm", digest_algorithm) if enduser_note is not None: pulumi.set(__self__, "enduser_note", enduser_note) if entity_key is not None: pulumi.set(__self__, "entity_key", entity_key) if entity_url is not None: pulumi.set(__self__, "entity_url", entity_url) if features is not None: pulumi.set(__self__, "features", features) if groups is not None: warnings.warn("""The direct configuration of groups in this app resource is deprecated, please ensure you use the resource `okta_app_group_assignments` for this functionality.""", DeprecationWarning) pulumi.log.warn("""groups is deprecated: The direct configuration of groups in this app resource is deprecated, please ensure you use the resource `okta_app_group_assignments` for this functionality.""") if groups is not None: pulumi.set(__self__, "groups", groups) if hide_ios is not None: pulumi.set(__self__, "hide_ios", hide_ios) if hide_web is not None: pulumi.set(__self__, "hide_web", hide_web) if honor_force_authn is not None: pulumi.set(__self__, "honor_force_authn", honor_force_authn) if http_post_binding is not None: pulumi.set(__self__, "http_post_binding", http_post_binding) if http_redirect_binding is not None: pulumi.set(__self__, "http_redirect_binding", http_redirect_binding) if idp_issuer is not None: pulumi.set(__self__, "idp_issuer", idp_issuer) if inline_hook_id is not None: pulumi.set(__self__, "inline_hook_id", inline_hook_id) if key_id is not None: pulumi.set(__self__, "key_id", key_id) if key_name is not None: pulumi.set(__self__, "key_name", key_name) if key_years_valid is not None: pulumi.set(__self__, "key_years_valid", key_years_valid) if label is not None: pulumi.set(__self__, "label", label) if logo is not None: pulumi.set(__self__, "logo", logo) if logo_url is not None: pulumi.set(__self__, "logo_url", logo_url) if metadata is not None: pulumi.set(__self__, "metadata", metadata) if metadata_url is not None: pulumi.set(__self__, "metadata_url", metadata_url) if name is not None: pulumi.set(__self__, "name", name) if preconfigured_app is not None: pulumi.set(__self__, "preconfigured_app", preconfigured_app) if recipient is not None: pulumi.set(__self__, "recipient", recipient) if request_compressed is not None: pulumi.set(__self__, "request_compressed", request_compressed) if response_signed is not None: pulumi.set(__self__, "response_signed", response_signed) if saml_version is not None: pulumi.set(__self__, "saml_version", saml_version) if sign_on_mode is not None: pulumi.set(__self__, "sign_on_mode", sign_on_mode) if signature_algorithm is not None: pulumi.set(__self__, "signature_algorithm", signature_algorithm) if single_logout_certificate is not None: pulumi.set(__self__, "single_logout_certificate", single_logout_certificate) if single_logout_issuer is not None: pulumi.set(__self__, "single_logout_issuer", single_logout_issuer) if single_logout_url is not None: pulumi.set(__self__, "single_logout_url", single_logout_url) if skip_groups is not None: pulumi.set(__self__, "skip_groups", skip_groups) if skip_users is not None: pulumi.set(__self__, "skip_users", skip_users) if sp_issuer is not None: pulumi.set(__self__, "sp_issuer", sp_issuer) if sso_url is not None: pulumi.set(__self__, "sso_url", sso_url) if status is not None: pulumi.set(__self__, "status", status) if subject_name_id_format is not None: pulumi.set(__self__, "subject_name_id_format", subject_name_id_format) if subject_name_id_template is not None: pulumi.set(__self__, "subject_name_id_template", subject_name_id_template) if user_name_template is not None: pulumi.set(__self__, "user_name_template", user_name_template) if user_name_template_suffix is not None: pulumi.set(__self__, "user_name_template_suffix", user_name_template_suffix) if user_name_template_type is not None: pulumi.set(__self__, "user_name_template_type", user_name_template_type) if users is not None: warnings.warn("""The direct configuration of users in this app resource is deprecated, please ensure you use the resource `okta_app_user` for this functionality.""", DeprecationWarning) pulumi.log.warn("""users is deprecated: The direct configuration of users in this app resource is deprecated, please ensure you use the resource `okta_app_user` for this functionality.""") if users is not None: pulumi.set(__self__, "users", users) @property @pulumi.getter(name="accessibilityErrorRedirectUrl") def accessibility_error_redirect_url(self) -> Optional[pulumi.Input[str]]: """ Custom error page URL. """ return pulumi.get(self, "accessibility_error_redirect_url") @accessibility_error_redirect_url.setter def accessibility_error_redirect_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "accessibility_error_redirect_url", value) @property @pulumi.getter(name="accessibilityLoginRedirectUrl") def accessibility_login_redirect_url(self) -> Optional[pulumi.Input[str]]: """ Custom login page for this application. """ return pulumi.get(self, "accessibility_login_redirect_url") @accessibility_login_redirect_url.setter def accessibility_login_redirect_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "accessibility_login_redirect_url", value) @property @pulumi.getter(name="accessibilitySelfService") def accessibility_self_service(self) -> Optional[pulumi.Input[bool]]: """ Enable self-service. By default, it is `false`. """ return pulumi.get(self, "accessibility_self_service") @accessibility_self_service.setter def accessibility_self_service(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "accessibility_self_service", value) @property @pulumi.getter(name="acsEndpoints") def acs_endpoints(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ An array of ACS endpoints. You can configure a maximum of 100 endpoints. """ return pulumi.get(self, "acs_endpoints") @acs_endpoints.setter def acs_endpoints(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "acs_endpoints", value) @property @pulumi.getter(name="adminNote") def admin_note(self) -> Optional[pulumi.Input[str]]: """ Application notes for admins. """ return pulumi.get(self, "admin_note") @admin_note.setter def admin_note(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "admin_note", value) @property @pulumi.getter(name="appLinksJson") def app_links_json(self) -> Optional[pulumi.Input[str]]: """ Displays specific appLinks for the app. The value for the link should be boolean. """ return pulumi.get(self, "app_links_json") @app_links_json.setter def app_links_json(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "app_links_json", value) @property @pulumi.getter(name="appSettingsJson") def app_settings_json(self) -> Optional[pulumi.Input[str]]: """ Application settings in JSON format. """ return pulumi.get(self, "app_settings_json") @app_settings_json.setter def app_settings_json(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "app_settings_json", value) @property @pulumi.getter(name="assertionSigned") def assertion_signed(self) -> Optional[pulumi.Input[bool]]: """ Determines whether the SAML assertion is digitally signed. """ return pulumi.get(self, "assertion_signed") @assertion_signed.setter def assertion_signed(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "assertion_signed", value) @property @pulumi.getter(name="attributeStatements") def attribute_statements(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['SamlAttributeStatementArgs']]]]: """ List of SAML Attribute statements. """ return pulumi.get(self, "attribute_statements") @attribute_statements.setter def attribute_statements(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['SamlAttributeStatementArgs']]]]): pulumi.set(self, "attribute_statements", value) @property @pulumi.getter def audience(self) -> Optional[pulumi.Input[str]]: """ Audience restriction. """ return pulumi.get(self, "audience") @audience.setter def audience(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "audience", value) @property @pulumi.getter(name="authnContextClassRef") def authn_context_class_ref(self) -> Optional[pulumi.Input[str]]: """ Identifies the SAML authentication context class for the assertion’s authentication statement. """ return pulumi.get(self, "authn_context_class_ref") @authn_context_class_ref.setter def authn_context_class_ref(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "authn_context_class_ref", value) @property @pulumi.getter(name="autoSubmitToolbar") def auto_submit_toolbar(self) -> Optional[pulumi.Input[bool]]: """ Display auto submit toolbar. """ return pulumi.get(self, "auto_submit_toolbar") @auto_submit_toolbar.setter def auto_submit_toolbar(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "auto_submit_toolbar", value) @property @pulumi.getter def certificate(self) -> Optional[pulumi.Input[str]]: """ The raw signing certificate. """ return pulumi.get(self, "certificate") @certificate.setter def certificate(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "certificate", value) @property @pulumi.getter(name="defaultRelayState") def default_relay_state(self) -> Optional[pulumi.Input[str]]: """ Identifies a specific application resource in an IDP initiated SSO scenario. """ return pulumi.get(self, "default_relay_state") @default_relay_state.setter def default_relay_state(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "default_relay_state", value) @property @pulumi.getter def destination(self) -> Optional[pulumi.Input[str]]: """ Identifies the location where the SAML response is intended to be sent inside the SAML assertion. """ return pulumi.get(self, "destination") @destination.setter def destination(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "destination", value) @property @pulumi.getter(name="digestAlgorithm") def digest_algorithm(self) -> Optional[pulumi.Input[str]]: """ Determines the digest algorithm used to digitally sign the SAML assertion and response. """ return pulumi.get(self, "digest_algorithm") @digest_algorithm.setter def digest_algorithm(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "digest_algorithm", value) @property @pulumi.getter(name="enduserNote") def enduser_note(self) -> Optional[pulumi.Input[str]]: """ Application notes for end users. """ return pulumi.get(self, "enduser_note") @enduser_note.setter def enduser_note(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "enduser_note", value) @property @pulumi.getter(name="entityKey") def entity_key(self) -> Optional[pulumi.Input[str]]: """ Entity ID, the ID portion of the `entity_url`. """ return pulumi.get(self, "entity_key") @entity_key.setter def entity_key(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "entity_key", value) @property @pulumi.getter(name="entityUrl") def entity_url(self) -> Optional[pulumi.Input[str]]: """ Entity URL for instance [http://www.okta.com/exk1fcia6d6EMsf331d8](http://www.okta.com/exk1fcia6d6EMsf331d8). """ return pulumi.get(self, "entity_url") @entity_url.setter def entity_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "entity_url", value) @property @pulumi.getter def features(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ features enabled. Notice: you can't currently configure provisioning features via the API. """ return pulumi.get(self, "features") @features.setter def features(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "features", value) @property @pulumi.getter def groups(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Groups associated with the application. - `DEPRECATED`: Please replace usage with the `AppGroupAssignments` (or `app.GroupAssignment`) resource. """ return pulumi.get(self, "groups") @groups.setter def groups(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "groups", value) @property @pulumi.getter(name="hideIos") def hide_ios(self) -> Optional[pulumi.Input[bool]]: """ Do not display application icon on mobile app. """ return pulumi.get(self, "hide_ios") @hide_ios.setter def hide_ios(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "hide_ios", value) @property @pulumi.getter(name="hideWeb") def hide_web(self) -> Optional[pulumi.Input[bool]]: """ Do not display application icon to users """ return pulumi.get(self, "hide_web") @hide_web.setter def hide_web(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "hide_web", value) @property @pulumi.getter(name="honorForceAuthn") def honor_force_authn(self) -> Optional[pulumi.Input[bool]]: """ Prompt user to re-authenticate if SP asks for it. """ return pulumi.get(self, "honor_force_authn") @honor_force_authn.setter def honor_force_authn(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "honor_force_authn", value) @property @pulumi.getter(name="httpPostBinding") def http_post_binding(self) -> Optional[pulumi.Input[str]]: """ `urn:oasis:names:tc:SAML:2.0:bindings:HTTP-Post` location from the SAML metadata. """ return pulumi.get(self, "http_post_binding") @http_post_binding.setter def http_post_binding(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "http_post_binding", value) @property @pulumi.getter(name="httpRedirectBinding") def http_redirect_binding(self) -> Optional[pulumi.Input[str]]: """ `urn:oasis:names:tc:SAML:2.0:bindings:HTTP-Redirect` location from the SAML metadata. """ return pulumi.get(self, "http_redirect_binding") @http_redirect_binding.setter def http_redirect_binding(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "http_redirect_binding", value) @property @pulumi.getter(name="idpIssuer") def idp_issuer(self) -> Optional[pulumi.Input[str]]: """ SAML issuer ID. """ return pulumi.get(self, "idp_issuer") @idp_issuer.setter def idp_issuer(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "idp_issuer", value) @property @pulumi.getter(name="inlineHookId") def inline_hook_id(self) -> Optional[pulumi.Input[str]]: """ Saml Inline Hook associated with the application. """ return pulumi.get(self, "inline_hook_id") @inline_hook_id.setter def inline_hook_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "inline_hook_id", value) @property @pulumi.getter(name="keyId") def key_id(self) -> Optional[pulumi.Input[str]]: """ Certificate key ID. """ return pulumi.get(self, "key_id") @key_id.setter def key_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "key_id", value) @property @pulumi.getter(name="keyName") def key_name(self) -> Optional[pulumi.Input[str]]: """ Certificate name. This modulates the rotation of keys. New name == new key. Required to be set with `key_years_valid`. """ return pulumi.get(self, "key_name") @key_name.setter def key_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "key_name", value) @property @pulumi.getter(name="keyYearsValid") def key_years_valid(self) -> Optional[pulumi.Input[int]]: """ Number of years the certificate is valid (2 - 10 years). """ return pulumi.get(self, "key_years_valid") @key_years_valid.setter def key_years_valid(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "key_years_valid", value) @property @pulumi.getter def label(self) -> Optional[pulumi.Input[str]]: """ label of application. """ return pulumi.get(self, "label") @label.setter def label(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "label", value) @property @pulumi.getter def logo(self) -> Optional[pulumi.Input[str]]: """ Local file path to the logo. The file must be in PNG, JPG, or GIF format, and less than 1 MB in size. """ return pulumi.get(self, "logo") @logo.setter def logo(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "logo", value) @property @pulumi.getter(name="logoUrl") def logo_url(self) -> Optional[pulumi.Input[str]]: """ Direct link of application logo. """ return pulumi.get(self, "logo_url") @logo_url.setter def logo_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "logo_url", value) @property @pulumi.getter def metadata(self) -> Optional[pulumi.Input[str]]: """ The raw SAML metadata in XML. """ return pulumi.get(self, "metadata") @metadata.setter def metadata(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "metadata", value) @property @pulumi.getter(name="metadataUrl") def metadata_url(self) -> Optional[pulumi.Input[str]]: """ SAML xml metadata URL. """ return pulumi.get(self, "metadata_url") @metadata_url.setter def metadata_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "metadata_url", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the attribute statement. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="preconfiguredApp") def preconfigured_app(self) -> Optional[pulumi.Input[str]]: """ name of application from the Okta Integration Network, if not included a custom app will be created. """ return pulumi.get(self, "preconfigured_app") @preconfigured_app.setter def preconfigured_app(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "preconfigured_app", value) @property @pulumi.getter def recipient(self) -> Optional[pulumi.Input[str]]: """ The location where the app may present the SAML assertion. """ return pulumi.get(self, "recipient") @recipient.setter def recipient(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "recipient", value) @property @pulumi.getter(name="requestCompressed") def request_compressed(self) -> Optional[pulumi.Input[bool]]: """ Denotes whether the request is compressed or not. """ return pulumi.get(self, "request_compressed") @request_compressed.setter def request_compressed(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "request_compressed", value) @property @pulumi.getter(name="responseSigned") def response_signed(self) -> Optional[pulumi.Input[bool]]: """ Determines whether the SAML auth response message is digitally signed. """ return pulumi.get(self, "response_signed") @response_signed.setter def response_signed(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "response_signed", value) @property @pulumi.getter(name="samlVersion") def saml_version(self) -> Optional[pulumi.Input[str]]: """ SAML version for the app's sign-on mode. Valid values are: `"2.0"` or `"1.1"`. Default is `"2.0"`. """ return pulumi.get(self, "saml_version") @saml_version.setter def saml_version(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "saml_version", value) @property @pulumi.getter(name="signOnMode") def sign_on_mode(self) -> Optional[pulumi.Input[str]]: """ Sign-on mode of application. """ return pulumi.get(self, "sign_on_mode") @sign_on_mode.setter def sign_on_mode(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "sign_on_mode", value) @property @pulumi.getter(name="signatureAlgorithm") def signature_algorithm(self) -> Optional[pulumi.Input[str]]: """ Signature algorithm used ot digitally sign the assertion and response. """ return pulumi.get(self, "signature_algorithm") @signature_algorithm.setter def signature_algorithm(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "signature_algorithm", value) @property @pulumi.getter(name="singleLogoutCertificate") def single_logout_certificate(self) -> Optional[pulumi.Input[str]]: """ x509 encoded certificate that the Service Provider uses to sign Single Logout requests. Note: should be provided without `-----BEGIN CERTIFICATE-----` and `-----END CERTIFICATE-----`, see [official documentation](https://developer.okta.com/docs/reference/api/apps/#service-provider-certificate). """ return pulumi.get(self, "single_logout_certificate") @single_logout_certificate.setter def single_logout_certificate(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "single_logout_certificate", value) @property @pulumi.getter(name="singleLogoutIssuer") def single_logout_issuer(self) -> Optional[pulumi.Input[str]]: """ The issuer of the Service Provider that generates the Single Logout request. """ return pulumi.get(self, "single_logout_issuer") @single_logout_issuer.setter def single_logout_issuer(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "single_logout_issuer", value) @property @pulumi.getter(name="singleLogoutUrl") def single_logout_url(self) -> Optional[pulumi.Input[str]]: """ The location where the logout response is sent. """ return pulumi.get(self, "single_logout_url") @single_logout_url.setter def single_logout_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "single_logout_url", value) @property @pulumi.getter(name="skipGroups") def skip_groups(self) -> Optional[pulumi.Input[bool]]: """ Indicator that allows the app to skip `groups` sync (it's also can be provided during import). Default is `false`. """ return pulumi.get(self, "skip_groups") @skip_groups.setter def skip_groups(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "skip_groups", value) @property @pulumi.getter(name="skipUsers") def skip_users(self) -> Optional[pulumi.Input[bool]]: """ Indicator that allows the app to skip `users` sync (it's also can be provided during import). Default is `false`. """ return pulumi.get(self, "skip_users") @skip_users.setter def skip_users(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "skip_users", value) @property @pulumi.getter(name="spIssuer") def sp_issuer(self) -> Optional[pulumi.Input[str]]: """ SAML service provider issuer. """ return pulumi.get(self, "sp_issuer") @sp_issuer.setter def sp_issuer(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "sp_issuer", value) @property @pulumi.getter(name="ssoUrl") def sso_url(self) -> Optional[pulumi.Input[str]]: """ Single Sign-on Url. """ return pulumi.get(self, "sso_url") @sso_url.setter def sso_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "sso_url", value) @property @pulumi.getter def status(self) -> Optional[pulumi.Input[str]]: """ status of application. """ return pulumi.get(self, "status") @status.setter def status(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "status", value) @property @pulumi.getter(name="subjectNameIdFormat") def subject_name_id_format(self) -> Optional[pulumi.Input[str]]: """ Identifies the SAML processing rules. """ return pulumi.get(self, "subject_name_id_format") @subject_name_id_format.setter def subject_name_id_format(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "subject_name_id_format", value) @property @pulumi.getter(name="subjectNameIdTemplate") def subject_name_id_template(self) -> Optional[pulumi.Input[str]]: """ Template for app user's username when a user is assigned to the app. """ return pulumi.get(self, "subject_name_id_template") @subject_name_id_template.setter def subject_name_id_template(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "subject_name_id_template", value) @property @pulumi.getter(name="userNameTemplate") def user_name_template(self) -> Optional[pulumi.Input[str]]: """ Username template. """ return pulumi.get(self, "user_name_template") @user_name_template.setter def user_name_template(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "user_name_template", value) @property @pulumi.getter(name="userNameTemplateSuffix") def user_name_template_suffix(self) -> Optional[pulumi.Input[str]]: """ Username template suffix. """ return pulumi.get(self, "user_name_template_suffix") @user_name_template_suffix.setter def user_name_template_suffix(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "user_name_template_suffix", value) @property @pulumi.getter(name="userNameTemplateType") def user_name_template_type(self) -> Optional[pulumi.Input[str]]: """ Username template type. """ return pulumi.get(self, "user_name_template_type") @user_name_template_type.setter def user_name_template_type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "user_name_template_type", value) @property @pulumi.getter def users(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['SamlUserArgs']]]]: """ Users associated with the application. - `DEPRECATED`: Please replace usage with the `app.User` resource. """ return pulumi.get(self, "users") @users.setter def users(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['SamlUserArgs']]]]): pulumi.set(self, "users", value) class Saml(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, accessibility_error_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_login_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_self_service: Optional[pulumi.Input[bool]] = None, acs_endpoints: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, admin_note: Optional[pulumi.Input[str]] = None, app_links_json: Optional[pulumi.Input[str]] = None, app_settings_json: Optional[pulumi.Input[str]] = None, assertion_signed: Optional[pulumi.Input[bool]] = None, attribute_statements: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlAttributeStatementArgs']]]]] = None, audience: Optional[pulumi.Input[str]] = None, authn_context_class_ref: Optional[pulumi.Input[str]] = None, auto_submit_toolbar: Optional[pulumi.Input[bool]] = None, default_relay_state: Optional[pulumi.Input[str]] = None, destination: Optional[pulumi.Input[str]] = None, digest_algorithm: Optional[pulumi.Input[str]] = None, enduser_note: Optional[pulumi.Input[str]] = None, features: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, hide_ios: Optional[pulumi.Input[bool]] = None, hide_web: Optional[pulumi.Input[bool]] = None, honor_force_authn: Optional[pulumi.Input[bool]] = None, idp_issuer: Optional[pulumi.Input[str]] = None, inline_hook_id: Optional[pulumi.Input[str]] = None, key_name: Optional[pulumi.Input[str]] = None, key_years_valid: Optional[pulumi.Input[int]] = None, label: Optional[pulumi.Input[str]] = None, logo: Optional[pulumi.Input[str]] = None, preconfigured_app: Optional[pulumi.Input[str]] = None, recipient: Optional[pulumi.Input[str]] = None, request_compressed: Optional[pulumi.Input[bool]] = None, response_signed: Optional[pulumi.Input[bool]] = None, saml_version: Optional[pulumi.Input[str]] = None, signature_algorithm: Optional[pulumi.Input[str]] = None, single_logout_certificate: Optional[pulumi.Input[str]] = None, single_logout_issuer: Optional[pulumi.Input[str]] = None, single_logout_url: Optional[pulumi.Input[str]] = None, skip_groups: Optional[pulumi.Input[bool]] = None, skip_users: Optional[pulumi.Input[bool]] = None, sp_issuer: Optional[pulumi.Input[str]] = None, sso_url: Optional[pulumi.Input[str]] = None, status: Optional[pulumi.Input[str]] = None, subject_name_id_format: Optional[pulumi.Input[str]] = None, subject_name_id_template: Optional[pulumi.Input[str]] = None, user_name_template: Optional[pulumi.Input[str]] = None, user_name_template_suffix: Optional[pulumi.Input[str]] = None, user_name_template_type: Optional[pulumi.Input[str]] = None, users: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlUserArgs']]]]] = None, __props__=None): """ Creates an SAML Application. This resource allows you to create and configure an SAML Application. ## Example Usage ```python import pulumi import pulumi_okta as okta example = okta.app.Saml("example", attribute_statements=[okta.app.SamlAttributeStatementArgs( filter_type="REGEX", filter_value=".*", name="groups", type="GROUP", )], audience="http://example.com/audience", authn_context_class_ref="urn:oasis:names:tc:SAML:2.0:ac:classes:PasswordProtectedTransport", destination="http://example.com", digest_algorithm="SHA256", honor_force_authn=False, label="example", recipient="http://example.com", response_signed=True, signature_algorithm="RSA_SHA256", sso_url="http://example.com", subject_name_id_format="urn:oasis:names:tc:SAML:1.1:nameid-format:emailAddress", subject_name_id_template=user["userName"]) ``` ### With inline hook ```python import pulumi import pulumi_okta as okta test_hook = okta.inline.Hook("testHook", status="ACTIVE", type="com.okta.saml.tokens.transform", version="1.0.2", channel={ "type": "HTTP", "version": "1.0.0", "uri": "https://example.com/test1", "method": "POST", }, auth={ "key": "Authorization", "type": "HEADER", "value": "secret", }) test_saml = okta.app.Saml("testSaml", label="testAcc_replace_with_uuid", sso_url="http://google.com", recipient="http://here.com", destination="http://its-about-the-journey.com", audience="http://audience.com", subject_name_id_template=user["userName"], subject_name_id_format="urn:oasis:names:tc:SAML:1.1:nameid-format:emailAddress", response_signed=True, signature_algorithm="RSA_SHA256", digest_algorithm="SHA256", honor_force_authn=False, authn_context_class_ref="urn:oasis:names:tc:SAML:2.0:ac:classes:PasswordProtectedTransport", inline_hook_id=test_hook.id, attribute_statements=[okta.app.SamlAttributeStatementArgs( type="GROUP", name="groups", filter_type="REGEX", filter_value=".*", )], opts=pulumi.ResourceOptions(depends_on=[test_hook])) ``` ### Pre-configured app with SAML 1.1 sign-on mode ```python import pulumi import pulumi_okta as okta test = okta.app.Saml("test", app_settings_json=\"\"\"{ "groupFilter": "app1.*", "siteURL": "http://www.okta.com" } \"\"\", label="SharePoint (On-Premise)", preconfigured_app="sharepoint_onpremise", saml_version="1.1", status="ACTIVE", user_name_template=source["login"], user_name_template_type="BUILT_IN") ``` ### Pre-configured app with SAML 1.1 sign-on mode, `app_settings_json` and `app_links_json` ```python import pulumi import pulumi_okta as okta office365 = okta.app.Saml("office365", app_links_json=\"\"\" { "calendar": false, "crm": false, "delve": false, "excel": false, "forms": false, "mail": false, "newsfeed": false, "onedrive": false, "people": false, "planner": false, "powerbi": false, "powerpoint": false, "sites": false, "sway": false, "tasks": false, "teams": false, "video": false, "word": false, "yammer": false, "login": true } \"\"\", app_settings_json=\"\"\" { "wsFedConfigureType": "AUTO", "windowsTransportEnabled": false, "domain": "okta.com", "msftTenant": "okta", "domains": [], "requireAdminConsent": false } \"\"\", label="Microsoft Office 365", preconfigured_app="office365", saml_version="1.1", status="ACTIVE") ``` ## Import A SAML App can be imported via the Okta ID. ```sh $ pulumi import okta:app/saml:Saml example <app id> ``` It's also possible to import app without groups or/and users. In this case ID may look like this ```sh $ pulumi import okta:app/saml:Saml example <app id>/skip_users ``` ```sh $ pulumi import okta:app/saml:Saml example <app id>/skip_users/skip_groups ``` ```sh $ pulumi import okta:app/saml:Saml example <app id>/skip_groups ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] accessibility_error_redirect_url: Custom error page URL. :param pulumi.Input[str] accessibility_login_redirect_url: Custom login page for this application. :param pulumi.Input[bool] accessibility_self_service: Enable self-service. By default, it is `false`. :param pulumi.Input[Sequence[pulumi.Input[str]]] acs_endpoints: An array of ACS endpoints. You can configure a maximum of 100 endpoints. :param pulumi.Input[str] admin_note: Application notes for admins. :param pulumi.Input[str] app_links_json: Displays specific appLinks for the app. The value for the link should be boolean. :param pulumi.Input[str] app_settings_json: Application settings in JSON format. :param pulumi.Input[bool] assertion_signed: Determines whether the SAML assertion is digitally signed. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlAttributeStatementArgs']]]] attribute_statements: List of SAML Attribute statements. :param pulumi.Input[str] audience: Audience restriction. :param pulumi.Input[str] authn_context_class_ref: Identifies the SAML authentication context class for the assertion’s authentication statement. :param pulumi.Input[bool] auto_submit_toolbar: Display auto submit toolbar. :param pulumi.Input[str] default_relay_state: Identifies a specific application resource in an IDP initiated SSO scenario. :param pulumi.Input[str] destination: Identifies the location where the SAML response is intended to be sent inside the SAML assertion. :param pulumi.Input[str] digest_algorithm: Determines the digest algorithm used to digitally sign the SAML assertion and response. :param pulumi.Input[str] enduser_note: Application notes for end users. :param pulumi.Input[Sequence[pulumi.Input[str]]] features: features enabled. Notice: you can't currently configure provisioning features via the API. :param pulumi.Input[Sequence[pulumi.Input[str]]] groups: Groups associated with the application. - `DEPRECATED`: Please replace usage with the `AppGroupAssignments` (or `app.GroupAssignment`) resource. :param pulumi.Input[bool] hide_ios: Do not display application icon on mobile app. :param pulumi.Input[bool] hide_web: Do not display application icon to users :param pulumi.Input[bool] honor_force_authn: Prompt user to re-authenticate if SP asks for it. :param pulumi.Input[str] idp_issuer: SAML issuer ID. :param pulumi.Input[str] inline_hook_id: Saml Inline Hook associated with the application. :param pulumi.Input[str] key_name: Certificate name. This modulates the rotation of keys. New name == new key. Required to be set with `key_years_valid`. :param pulumi.Input[int] key_years_valid: Number of years the certificate is valid (2 - 10 years). :param pulumi.Input[str] label: label of application. :param pulumi.Input[str] logo: Local file path to the logo. The file must be in PNG, JPG, or GIF format, and less than 1 MB in size. :param pulumi.Input[str] preconfigured_app: name of application from the Okta Integration Network, if not included a custom app will be created. :param pulumi.Input[str] recipient: The location where the app may present the SAML assertion. :param pulumi.Input[bool] request_compressed: Denotes whether the request is compressed or not. :param pulumi.Input[bool] response_signed: Determines whether the SAML auth response message is digitally signed. :param pulumi.Input[str] saml_version: SAML version for the app's sign-on mode. Valid values are: `"2.0"` or `"1.1"`. Default is `"2.0"`. :param pulumi.Input[str] signature_algorithm: Signature algorithm used ot digitally sign the assertion and response. :param pulumi.Input[str] single_logout_certificate: x509 encoded certificate that the Service Provider uses to sign Single Logout requests. Note: should be provided without `-----BEGIN CERTIFICATE-----` and `-----END CERTIFICATE-----`, see [official documentation](https://developer.okta.com/docs/reference/api/apps/#service-provider-certificate). :param pulumi.Input[str] single_logout_issuer: The issuer of the Service Provider that generates the Single Logout request. :param pulumi.Input[str] single_logout_url: The location where the logout response is sent. :param pulumi.Input[bool] skip_groups: Indicator that allows the app to skip `groups` sync (it's also can be provided during import). Default is `false`. :param pulumi.Input[bool] skip_users: Indicator that allows the app to skip `users` sync (it's also can be provided during import). Default is `false`. :param pulumi.Input[str] sp_issuer: SAML service provider issuer. :param pulumi.Input[str] sso_url: Single Sign-on Url. :param pulumi.Input[str] status: status of application. :param pulumi.Input[str] subject_name_id_format: Identifies the SAML processing rules. :param pulumi.Input[str] subject_name_id_template: Template for app user's username when a user is assigned to the app. :param pulumi.Input[str] user_name_template: Username template. :param pulumi.Input[str] user_name_template_suffix: Username template suffix. :param pulumi.Input[str] user_name_template_type: Username template type. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlUserArgs']]]] users: Users associated with the application. - `DEPRECATED`: Please replace usage with the `app.User` resource. """ ... @overload def __init__(__self__, resource_name: str, args: SamlArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Creates an SAML Application. This resource allows you to create and configure an SAML Application. ## Example Usage ```python import pulumi import pulumi_okta as okta example = okta.app.Saml("example", attribute_statements=[okta.app.SamlAttributeStatementArgs( filter_type="REGEX", filter_value=".*", name="groups", type="GROUP", )], audience="http://example.com/audience", authn_context_class_ref="urn:oasis:names:tc:SAML:2.0:ac:classes:PasswordProtectedTransport", destination="http://example.com", digest_algorithm="SHA256", honor_force_authn=False, label="example", recipient="http://example.com", response_signed=True, signature_algorithm="RSA_SHA256", sso_url="http://example.com", subject_name_id_format="urn:oasis:names:tc:SAML:1.1:nameid-format:emailAddress", subject_name_id_template=user["userName"]) ``` ### With inline hook ```python import pulumi import pulumi_okta as okta test_hook = okta.inline.Hook("testHook", status="ACTIVE", type="com.okta.saml.tokens.transform", version="1.0.2", channel={ "type": "HTTP", "version": "1.0.0", "uri": "https://example.com/test1", "method": "POST", }, auth={ "key": "Authorization", "type": "HEADER", "value": "secret", }) test_saml = okta.app.Saml("testSaml", label="testAcc_replace_with_uuid", sso_url="http://google.com", recipient="http://here.com", destination="http://its-about-the-journey.com", audience="http://audience.com", subject_name_id_template=user["userName"], subject_name_id_format="urn:oasis:names:tc:SAML:1.1:nameid-format:emailAddress", response_signed=True, signature_algorithm="RSA_SHA256", digest_algorithm="SHA256", honor_force_authn=False, authn_context_class_ref="urn:oasis:names:tc:SAML:2.0:ac:classes:PasswordProtectedTransport", inline_hook_id=test_hook.id, attribute_statements=[okta.app.SamlAttributeStatementArgs( type="GROUP", name="groups", filter_type="REGEX", filter_value=".*", )], opts=pulumi.ResourceOptions(depends_on=[test_hook])) ``` ### Pre-configured app with SAML 1.1 sign-on mode ```python import pulumi import pulumi_okta as okta test = okta.app.Saml("test", app_settings_json=\"\"\"{ "groupFilter": "app1.*", "siteURL": "http://www.okta.com" } \"\"\", label="SharePoint (On-Premise)", preconfigured_app="sharepoint_onpremise", saml_version="1.1", status="ACTIVE", user_name_template=source["login"], user_name_template_type="BUILT_IN") ``` ### Pre-configured app with SAML 1.1 sign-on mode, `app_settings_json` and `app_links_json` ```python import pulumi import pulumi_okta as okta office365 = okta.app.Saml("office365", app_links_json=\"\"\" { "calendar": false, "crm": false, "delve": false, "excel": false, "forms": false, "mail": false, "newsfeed": false, "onedrive": false, "people": false, "planner": false, "powerbi": false, "powerpoint": false, "sites": false, "sway": false, "tasks": false, "teams": false, "video": false, "word": false, "yammer": false, "login": true } \"\"\", app_settings_json=\"\"\" { "wsFedConfigureType": "AUTO", "windowsTransportEnabled": false, "domain": "okta.com", "msftTenant": "okta", "domains": [], "requireAdminConsent": false } \"\"\", label="Microsoft Office 365", preconfigured_app="office365", saml_version="1.1", status="ACTIVE") ``` ## Import A SAML App can be imported via the Okta ID. ```sh $ pulumi import okta:app/saml:Saml example <app id> ``` It's also possible to import app without groups or/and users. In this case ID may look like this ```sh $ pulumi import okta:app/saml:Saml example <app id>/skip_users ``` ```sh $ pulumi import okta:app/saml:Saml example <app id>/skip_users/skip_groups ``` ```sh $ pulumi import okta:app/saml:Saml example <app id>/skip_groups ``` :param str resource_name: The name of the resource. :param SamlArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(SamlArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, accessibility_error_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_login_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_self_service: Optional[pulumi.Input[bool]] = None, acs_endpoints: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, admin_note: Optional[pulumi.Input[str]] = None, app_links_json: Optional[pulumi.Input[str]] = None, app_settings_json: Optional[pulumi.Input[str]] = None, assertion_signed: Optional[pulumi.Input[bool]] = None, attribute_statements: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlAttributeStatementArgs']]]]] = None, audience: Optional[pulumi.Input[str]] = None, authn_context_class_ref: Optional[pulumi.Input[str]] = None, auto_submit_toolbar: Optional[pulumi.Input[bool]] = None, default_relay_state: Optional[pulumi.Input[str]] = None, destination: Optional[pulumi.Input[str]] = None, digest_algorithm: Optional[pulumi.Input[str]] = None, enduser_note: Optional[pulumi.Input[str]] = None, features: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, hide_ios: Optional[pulumi.Input[bool]] = None, hide_web: Optional[pulumi.Input[bool]] = None, honor_force_authn: Optional[pulumi.Input[bool]] = None, idp_issuer: Optional[pulumi.Input[str]] = None, inline_hook_id: Optional[pulumi.Input[str]] = None, key_name: Optional[pulumi.Input[str]] = None, key_years_valid: Optional[pulumi.Input[int]] = None, label: Optional[pulumi.Input[str]] = None, logo: Optional[pulumi.Input[str]] = None, preconfigured_app: Optional[pulumi.Input[str]] = None, recipient: Optional[pulumi.Input[str]] = None, request_compressed: Optional[pulumi.Input[bool]] = None, response_signed: Optional[pulumi.Input[bool]] = None, saml_version: Optional[pulumi.Input[str]] = None, signature_algorithm: Optional[pulumi.Input[str]] = None, single_logout_certificate: Optional[pulumi.Input[str]] = None, single_logout_issuer: Optional[pulumi.Input[str]] = None, single_logout_url: Optional[pulumi.Input[str]] = None, skip_groups: Optional[pulumi.Input[bool]] = None, skip_users: Optional[pulumi.Input[bool]] = None, sp_issuer: Optional[pulumi.Input[str]] = None, sso_url: Optional[pulumi.Input[str]] = None, status: Optional[pulumi.Input[str]] = None, subject_name_id_format: Optional[pulumi.Input[str]] = None, subject_name_id_template: Optional[pulumi.Input[str]] = None, user_name_template: Optional[pulumi.Input[str]] = None, user_name_template_suffix: Optional[pulumi.Input[str]] = None, user_name_template_type: Optional[pulumi.Input[str]] = None, users: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlUserArgs']]]]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = SamlArgs.__new__(SamlArgs) __props__.__dict__["accessibility_error_redirect_url"] = accessibility_error_redirect_url __props__.__dict__["accessibility_login_redirect_url"] = accessibility_login_redirect_url __props__.__dict__["accessibility_self_service"] = accessibility_self_service __props__.__dict__["acs_endpoints"] = acs_endpoints __props__.__dict__["admin_note"] = admin_note __props__.__dict__["app_links_json"] = app_links_json __props__.__dict__["app_settings_json"] = app_settings_json __props__.__dict__["assertion_signed"] = assertion_signed __props__.__dict__["attribute_statements"] = attribute_statements __props__.__dict__["audience"] = audience __props__.__dict__["authn_context_class_ref"] = authn_context_class_ref __props__.__dict__["auto_submit_toolbar"] = auto_submit_toolbar __props__.__dict__["default_relay_state"] = default_relay_state __props__.__dict__["destination"] = destination __props__.__dict__["digest_algorithm"] = digest_algorithm __props__.__dict__["enduser_note"] = enduser_note __props__.__dict__["features"] = features if groups is not None and not opts.urn: warnings.warn("""The direct configuration of groups in this app resource is deprecated, please ensure you use the resource `okta_app_group_assignments` for this functionality.""", DeprecationWarning) pulumi.log.warn("""groups is deprecated: The direct configuration of groups in this app resource is deprecated, please ensure you use the resource `okta_app_group_assignments` for this functionality.""") __props__.__dict__["groups"] = groups __props__.__dict__["hide_ios"] = hide_ios __props__.__dict__["hide_web"] = hide_web __props__.__dict__["honor_force_authn"] = honor_force_authn __props__.__dict__["idp_issuer"] = idp_issuer __props__.__dict__["inline_hook_id"] = inline_hook_id __props__.__dict__["key_name"] = key_name __props__.__dict__["key_years_valid"] = key_years_valid if label is None and not opts.urn: raise TypeError("Missing required property 'label'") __props__.__dict__["label"] = label __props__.__dict__["logo"] = logo __props__.__dict__["preconfigured_app"] = preconfigured_app __props__.__dict__["recipient"] = recipient __props__.__dict__["request_compressed"] = request_compressed __props__.__dict__["response_signed"] = response_signed __props__.__dict__["saml_version"] = saml_version __props__.__dict__["signature_algorithm"] = signature_algorithm __props__.__dict__["single_logout_certificate"] = single_logout_certificate __props__.__dict__["single_logout_issuer"] = single_logout_issuer __props__.__dict__["single_logout_url"] = single_logout_url __props__.__dict__["skip_groups"] = skip_groups __props__.__dict__["skip_users"] = skip_users __props__.__dict__["sp_issuer"] = sp_issuer __props__.__dict__["sso_url"] = sso_url __props__.__dict__["status"] = status __props__.__dict__["subject_name_id_format"] = subject_name_id_format __props__.__dict__["subject_name_id_template"] = subject_name_id_template __props__.__dict__["user_name_template"] = user_name_template __props__.__dict__["user_name_template_suffix"] = user_name_template_suffix __props__.__dict__["user_name_template_type"] = user_name_template_type if users is not None and not opts.urn: warnings.warn("""The direct configuration of users in this app resource is deprecated, please ensure you use the resource `okta_app_user` for this functionality.""", DeprecationWarning) pulumi.log.warn("""users is deprecated: The direct configuration of users in this app resource is deprecated, please ensure you use the resource `okta_app_user` for this functionality.""") __props__.__dict__["users"] = users __props__.__dict__["certificate"] = None __props__.__dict__["entity_key"] = None __props__.__dict__["entity_url"] = None __props__.__dict__["http_post_binding"] = None __props__.__dict__["http_redirect_binding"] = None __props__.__dict__["key_id"] = None __props__.__dict__["logo_url"] = None __props__.__dict__["metadata"] = None __props__.__dict__["metadata_url"] = None __props__.__dict__["name"] = None __props__.__dict__["sign_on_mode"] = None super(Saml, __self__).__init__( 'okta:app/saml:Saml', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, accessibility_error_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_login_redirect_url: Optional[pulumi.Input[str]] = None, accessibility_self_service: Optional[pulumi.Input[bool]] = None, acs_endpoints: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, admin_note: Optional[pulumi.Input[str]] = None, app_links_json: Optional[pulumi.Input[str]] = None, app_settings_json: Optional[pulumi.Input[str]] = None, assertion_signed: Optional[pulumi.Input[bool]] = None, attribute_statements: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlAttributeStatementArgs']]]]] = None, audience: Optional[pulumi.Input[str]] = None, authn_context_class_ref: Optional[pulumi.Input[str]] = None, auto_submit_toolbar: Optional[pulumi.Input[bool]] = None, certificate: Optional[pulumi.Input[str]] = None, default_relay_state: Optional[pulumi.Input[str]] = None, destination: Optional[pulumi.Input[str]] = None, digest_algorithm: Optional[pulumi.Input[str]] = None, enduser_note: Optional[pulumi.Input[str]] = None, entity_key: Optional[pulumi.Input[str]] = None, entity_url: Optional[pulumi.Input[str]] = None, features: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, hide_ios: Optional[pulumi.Input[bool]] = None, hide_web: Optional[pulumi.Input[bool]] = None, honor_force_authn: Optional[pulumi.Input[bool]] = None, http_post_binding: Optional[pulumi.Input[str]] = None, http_redirect_binding: Optional[pulumi.Input[str]] = None, idp_issuer: Optional[pulumi.Input[str]] = None, inline_hook_id: Optional[pulumi.Input[str]] = None, key_id: Optional[pulumi.Input[str]] = None, key_name: Optional[pulumi.Input[str]] = None, key_years_valid: Optional[pulumi.Input[int]] = None, label: Optional[pulumi.Input[str]] = None, logo: Optional[pulumi.Input[str]] = None, logo_url: Optional[pulumi.Input[str]] = None, metadata: Optional[pulumi.Input[str]] = None, metadata_url: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, preconfigured_app: Optional[pulumi.Input[str]] = None, recipient: Optional[pulumi.Input[str]] = None, request_compressed: Optional[pulumi.Input[bool]] = None, response_signed: Optional[pulumi.Input[bool]] = None, saml_version: Optional[pulumi.Input[str]] = None, sign_on_mode: Optional[pulumi.Input[str]] = None, signature_algorithm: Optional[pulumi.Input[str]] = None, single_logout_certificate: Optional[pulumi.Input[str]] = None, single_logout_issuer: Optional[pulumi.Input[str]] = None, single_logout_url: Optional[pulumi.Input[str]] = None, skip_groups: Optional[pulumi.Input[bool]] = None, skip_users: Optional[pulumi.Input[bool]] = None, sp_issuer: Optional[pulumi.Input[str]] = None, sso_url: Optional[pulumi.Input[str]] = None, status: Optional[pulumi.Input[str]] = None, subject_name_id_format: Optional[pulumi.Input[str]] = None, subject_name_id_template: Optional[pulumi.Input[str]] = None, user_name_template: Optional[pulumi.Input[str]] = None, user_name_template_suffix: Optional[pulumi.Input[str]] = None, user_name_template_type: Optional[pulumi.Input[str]] = None, users: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlUserArgs']]]]] = None) -> 'Saml': """ Get an existing Saml resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] accessibility_error_redirect_url: Custom error page URL. :param pulumi.Input[str] accessibility_login_redirect_url: Custom login page for this application. :param pulumi.Input[bool] accessibility_self_service: Enable self-service. By default, it is `false`. :param pulumi.Input[Sequence[pulumi.Input[str]]] acs_endpoints: An array of ACS endpoints. You can configure a maximum of 100 endpoints. :param pulumi.Input[str] admin_note: Application notes for admins. :param pulumi.Input[str] app_links_json: Displays specific appLinks for the app. The value for the link should be boolean. :param pulumi.Input[str] app_settings_json: Application settings in JSON format. :param pulumi.Input[bool] assertion_signed: Determines whether the SAML assertion is digitally signed. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlAttributeStatementArgs']]]] attribute_statements: List of SAML Attribute statements. :param pulumi.Input[str] audience: Audience restriction. :param pulumi.Input[str] authn_context_class_ref: Identifies the SAML authentication context class for the assertion’s authentication statement. :param pulumi.Input[bool] auto_submit_toolbar: Display auto submit toolbar. :param pulumi.Input[str] certificate: The raw signing certificate. :param pulumi.Input[str] default_relay_state: Identifies a specific application resource in an IDP initiated SSO scenario. :param pulumi.Input[str] destination: Identifies the location where the SAML response is intended to be sent inside the SAML assertion. :param pulumi.Input[str] digest_algorithm: Determines the digest algorithm used to digitally sign the SAML assertion and response. :param pulumi.Input[str] enduser_note: Application notes for end users. :param pulumi.Input[str] entity_key: Entity ID, the ID portion of the `entity_url`. :param pulumi.Input[str] entity_url: Entity URL for instance [http://www.okta.com/exk1fcia6d6EMsf331d8](http://www.okta.com/exk1fcia6d6EMsf331d8). :param pulumi.Input[Sequence[pulumi.Input[str]]] features: features enabled. Notice: you can't currently configure provisioning features via the API. :param pulumi.Input[Sequence[pulumi.Input[str]]] groups: Groups associated with the application. - `DEPRECATED`: Please replace usage with the `AppGroupAssignments` (or `app.GroupAssignment`) resource. :param pulumi.Input[bool] hide_ios: Do not display application icon on mobile app. :param pulumi.Input[bool] hide_web: Do not display application icon to users :param pulumi.Input[bool] honor_force_authn: Prompt user to re-authenticate if SP asks for it. :param pulumi.Input[str] http_post_binding: `urn:oasis:names:tc:SAML:2.0:bindings:HTTP-Post` location from the SAML metadata. :param pulumi.Input[str] http_redirect_binding: `urn:oasis:names:tc:SAML:2.0:bindings:HTTP-Redirect` location from the SAML metadata. :param pulumi.Input[str] idp_issuer: SAML issuer ID. :param pulumi.Input[str] inline_hook_id: Saml Inline Hook associated with the application. :param pulumi.Input[str] key_id: Certificate key ID. :param pulumi.Input[str] key_name: Certificate name. This modulates the rotation of keys. New name == new key. Required to be set with `key_years_valid`. :param pulumi.Input[int] key_years_valid: Number of years the certificate is valid (2 - 10 years). :param pulumi.Input[str] label: label of application. :param pulumi.Input[str] logo: Local file path to the logo. The file must be in PNG, JPG, or GIF format, and less than 1 MB in size. :param pulumi.Input[str] logo_url: Direct link of application logo. :param pulumi.Input[str] metadata: The raw SAML metadata in XML. :param pulumi.Input[str] metadata_url: SAML xml metadata URL. :param pulumi.Input[str] name: The name of the attribute statement. :param pulumi.Input[str] preconfigured_app: name of application from the Okta Integration Network, if not included a custom app will be created. :param pulumi.Input[str] recipient: The location where the app may present the SAML assertion. :param pulumi.Input[bool] request_compressed: Denotes whether the request is compressed or not. :param pulumi.Input[bool] response_signed: Determines whether the SAML auth response message is digitally signed. :param pulumi.Input[str] saml_version: SAML version for the app's sign-on mode. Valid values are: `"2.0"` or `"1.1"`. Default is `"2.0"`. :param pulumi.Input[str] sign_on_mode: Sign-on mode of application. :param pulumi.Input[str] signature_algorithm: Signature algorithm used ot digitally sign the assertion and response. :param pulumi.Input[str] single_logout_certificate: x509 encoded certificate that the Service Provider uses to sign Single Logout requests. Note: should be provided without `-----BEGIN CERTIFICATE-----` and `-----END CERTIFICATE-----`, see [official documentation](https://developer.okta.com/docs/reference/api/apps/#service-provider-certificate). :param pulumi.Input[str] single_logout_issuer: The issuer of the Service Provider that generates the Single Logout request. :param pulumi.Input[str] single_logout_url: The location where the logout response is sent. :param pulumi.Input[bool] skip_groups: Indicator that allows the app to skip `groups` sync (it's also can be provided during import). Default is `false`. :param pulumi.Input[bool] skip_users: Indicator that allows the app to skip `users` sync (it's also can be provided during import). Default is `false`. :param pulumi.Input[str] sp_issuer: SAML service provider issuer. :param pulumi.Input[str] sso_url: Single Sign-on Url. :param pulumi.Input[str] status: status of application. :param pulumi.Input[str] subject_name_id_format: Identifies the SAML processing rules. :param pulumi.Input[str] subject_name_id_template: Template for app user's username when a user is assigned to the app. :param pulumi.Input[str] user_name_template: Username template. :param pulumi.Input[str] user_name_template_suffix: Username template suffix. :param pulumi.Input[str] user_name_template_type: Username template type. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['SamlUserArgs']]]] users: Users associated with the application. - `DEPRECATED`: Please replace usage with the `app.User` resource. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _SamlState.__new__(_SamlState) __props__.__dict__["accessibility_error_redirect_url"] = accessibility_error_redirect_url __props__.__dict__["accessibility_login_redirect_url"] = accessibility_login_redirect_url __props__.__dict__["accessibility_self_service"] = accessibility_self_service __props__.__dict__["acs_endpoints"] = acs_endpoints __props__.__dict__["admin_note"] = admin_note __props__.__dict__["app_links_json"] = app_links_json __props__.__dict__["app_settings_json"] = app_settings_json __props__.__dict__["assertion_signed"] = assertion_signed __props__.__dict__["attribute_statements"] = attribute_statements __props__.__dict__["audience"] = audience __props__.__dict__["authn_context_class_ref"] = authn_context_class_ref __props__.__dict__["auto_submit_toolbar"] = auto_submit_toolbar __props__.__dict__["certificate"] = certificate __props__.__dict__["default_relay_state"] = default_relay_state __props__.__dict__["destination"] = destination __props__.__dict__["digest_algorithm"] = digest_algorithm __props__.__dict__["enduser_note"] = enduser_note __props__.__dict__["entity_key"] = entity_key __props__.__dict__["entity_url"] = entity_url __props__.__dict__["features"] = features __props__.__dict__["groups"] = groups __props__.__dict__["hide_ios"] = hide_ios __props__.__dict__["hide_web"] = hide_web __props__.__dict__["honor_force_authn"] = honor_force_authn __props__.__dict__["http_post_binding"] = http_post_binding __props__.__dict__["http_redirect_binding"] = http_redirect_binding __props__.__dict__["idp_issuer"] = idp_issuer __props__.__dict__["inline_hook_id"] = inline_hook_id __props__.__dict__["key_id"] = key_id __props__.__dict__["key_name"] = key_name __props__.__dict__["key_years_valid"] = key_years_valid __props__.__dict__["label"] = label __props__.__dict__["logo"] = logo __props__.__dict__["logo_url"] = logo_url __props__.__dict__["metadata"] = metadata __props__.__dict__["metadata_url"] = metadata_url __props__.__dict__["name"] = name __props__.__dict__["preconfigured_app"] = preconfigured_app __props__.__dict__["recipient"] = recipient __props__.__dict__["request_compressed"] = request_compressed __props__.__dict__["response_signed"] = response_signed __props__.__dict__["saml_version"] = saml_version __props__.__dict__["sign_on_mode"] = sign_on_mode __props__.__dict__["signature_algorithm"] = signature_algorithm __props__.__dict__["single_logout_certificate"] = single_logout_certificate __props__.__dict__["single_logout_issuer"] = single_logout_issuer __props__.__dict__["single_logout_url"] = single_logout_url __props__.__dict__["skip_groups"] = skip_groups __props__.__dict__["skip_users"] = skip_users __props__.__dict__["sp_issuer"] = sp_issuer __props__.__dict__["sso_url"] = sso_url __props__.__dict__["status"] = status __props__.__dict__["subject_name_id_format"] = subject_name_id_format __props__.__dict__["subject_name_id_template"] = subject_name_id_template __props__.__dict__["user_name_template"] = user_name_template __props__.__dict__["user_name_template_suffix"] = user_name_template_suffix __props__.__dict__["user_name_template_type"] = user_name_template_type __props__.__dict__["users"] = users return Saml(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="accessibilityErrorRedirectUrl") def accessibility_error_redirect_url(self) -> pulumi.Output[Optional[str]]: """ Custom error page URL. """ return pulumi.get(self, "accessibility_error_redirect_url") @property @pulumi.getter(name="accessibilityLoginRedirectUrl") def accessibility_login_redirect_url(self) -> pulumi.Output[Optional[str]]: """ Custom login page for this application. """ return pulumi.get(self, "accessibility_login_redirect_url") @property @pulumi.getter(name="accessibilitySelfService") def accessibility_self_service(self) -> pulumi.Output[Optional[bool]]: """ Enable self-service. By default, it is `false`. """ return pulumi.get(self, "accessibility_self_service") @property @pulumi.getter(name="acsEndpoints") def acs_endpoints(self) -> pulumi.Output[Optional[Sequence[str]]]: """ An array of ACS endpoints. You can configure a maximum of 100 endpoints. """ return pulumi.get(self, "acs_endpoints") @property @pulumi.getter(name="adminNote") def admin_note(self) -> pulumi.Output[Optional[str]]: """ Application notes for admins. """ return pulumi.get(self, "admin_note") @property @pulumi.getter(name="appLinksJson") def app_links_json(self) -> pulumi.Output[Optional[str]]: """ Displays specific appLinks for the app. The value for the link should be boolean. """ return pulumi.get(self, "app_links_json") @property @pulumi.getter(name="appSettingsJson") def app_settings_json(self) -> pulumi.Output[Optional[str]]: """ Application settings in JSON format. """ return pulumi.get(self, "app_settings_json") @property @pulumi.getter(name="assertionSigned") def assertion_signed(self) -> pulumi.Output[Optional[bool]]: """ Determines whether the SAML assertion is digitally signed. """ return pulumi.get(self, "assertion_signed") @property @pulumi.getter(name="attributeStatements") def attribute_statements(self) -> pulumi.Output[Optional[Sequence['outputs.SamlAttributeStatement']]]: """ List of SAML Attribute statements. """ return pulumi.get(self, "attribute_statements") @property @pulumi.getter def audience(self) -> pulumi.Output[Optional[str]]: """ Audience restriction. """ return pulumi.get(self, "audience") @property @pulumi.getter(name="authnContextClassRef") def authn_context_class_ref(self) -> pulumi.Output[Optional[str]]: """ Identifies the SAML authentication context class for the assertion’s authentication statement. """ return pulumi.get(self, "authn_context_class_ref") @property @pulumi.getter(name="autoSubmitToolbar") def auto_submit_toolbar(self) -> pulumi.Output[Optional[bool]]: """ Display auto submit toolbar. """ return pulumi.get(self, "auto_submit_toolbar") @property @pulumi.getter def certificate(self) -> pulumi.Output[str]: """ The raw signing certificate. """ return pulumi.get(self, "certificate") @property @pulumi.getter(name="defaultRelayState") def default_relay_state(self) -> pulumi.Output[Optional[str]]: """ Identifies a specific application resource in an IDP initiated SSO scenario. """ return pulumi.get(self, "default_relay_state") @property @pulumi.getter def destination(self) -> pulumi.Output[Optional[str]]: """ Identifies the location where the SAML response is intended to be sent inside the SAML assertion. """ return pulumi.get(self, "destination") @property @pulumi.getter(name="digestAlgorithm") def digest_algorithm(self) -> pulumi.Output[Optional[str]]: """ Determines the digest algorithm used to digitally sign the SAML assertion and response. """ return pulumi.get(self, "digest_algorithm") @property @pulumi.getter(name="enduserNote") def enduser_note(self) -> pulumi.Output[Optional[str]]: """ Application notes for end users. """ return pulumi.get(self, "enduser_note") @property @pulumi.getter(name="entityKey") def entity_key(self) -> pulumi.Output[str]: """ Entity ID, the ID portion of the `entity_url`. """ return pulumi.get(self, "entity_key") @property @pulumi.getter(name="entityUrl") def entity_url(self) -> pulumi.Output[str]: """ Entity URL for instance [http://www.okta.com/exk1fcia6d6EMsf331d8](http://www.okta.com/exk1fcia6d6EMsf331d8). """ return pulumi.get(self, "entity_url") @property @pulumi.getter def features(self) -> pulumi.Output[Optional[Sequence[str]]]: """ features enabled. Notice: you can't currently configure provisioning features via the API. """ return pulumi.get(self, "features") @property @pulumi.getter def groups(self) -> pulumi.Output[Optional[Sequence[str]]]: """ Groups associated with the application. - `DEPRECATED`: Please replace usage with the `AppGroupAssignments` (or `app.GroupAssignment`) resource. """ return pulumi.get(self, "groups") @property @pulumi.getter(name="hideIos") def hide_ios(self) -> pulumi.Output[Optional[bool]]: """ Do not display application icon on mobile app. """ return pulumi.get(self, "hide_ios") @property @pulumi.getter(name="hideWeb") def hide_web(self) -> pulumi.Output[Optional[bool]]: """ Do not display application icon to users """ return pulumi.get(self, "hide_web") @property @pulumi.getter(name="honorForceAuthn") def honor_force_authn(self) -> pulumi.Output[Optional[bool]]: """ Prompt user to re-authenticate if SP asks for it. """ return pulumi.get(self, "honor_force_authn") @property @pulumi.getter(name="httpPostBinding") def http_post_binding(self) -> pulumi.Output[str]: """ `urn:oasis:names:tc:SAML:2.0:bindings:HTTP-Post` location from the SAML metadata. """ return pulumi.get(self, "http_post_binding") @property @pulumi.getter(name="httpRedirectBinding") def http_redirect_binding(self) -> pulumi.Output[str]: """ `urn:oasis:names:tc:SAML:2.0:bindings:HTTP-Redirect` location from the SAML metadata. """ return pulumi.get(self, "http_redirect_binding") @property @pulumi.getter(name="idpIssuer") def idp_issuer(self) -> pulumi.Output[Optional[str]]: """ SAML issuer ID. """ return pulumi.get(self, "idp_issuer") @property @pulumi.getter(name="inlineHookId") def inline_hook_id(self) -> pulumi.Output[Optional[str]]: """ Saml Inline Hook associated with the application. """ return pulumi.get(self, "inline_hook_id") @property @pulumi.getter(name="keyId") def key_id(self) -> pulumi.Output[str]: """ Certificate key ID. """ return pulumi.get(self, "key_id") @property @pulumi.getter(name="keyName") def key_name(self) -> pulumi.Output[Optional[str]]: """ Certificate name. This modulates the rotation of keys. New name == new key. Required to be set with `key_years_valid`. """ return pulumi.get(self, "key_name") @property @pulumi.getter(name="keyYearsValid") def key_years_valid(self) -> pulumi.Output[Optional[int]]: """ Number of years the certificate is valid (2 - 10 years). """ return pulumi.get(self, "key_years_valid") @property @pulumi.getter def label(self) -> pulumi.Output[str]: """ label of application. """ return pulumi.get(self, "label") @property @pulumi.getter def logo(self) -> pulumi.Output[Optional[str]]: """ Local file path to the logo. The file must be in PNG, JPG, or GIF format, and less than 1 MB in size. """ return pulumi.get(self, "logo") @property @pulumi.getter(name="logoUrl") def logo_url(self) -> pulumi.Output[str]: """ Direct link of application logo. """ return pulumi.get(self, "logo_url") @property @pulumi.getter def metadata(self) -> pulumi.Output[str]: """ The raw SAML metadata in XML. """ return pulumi.get(self, "metadata") @property @pulumi.getter(name="metadataUrl") def metadata_url(self) -> pulumi.Output[str]: """ SAML xml metadata URL. """ return pulumi.get(self, "metadata_url") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The name of the attribute statement. """ return pulumi.get(self, "name") @property @pulumi.getter(name="preconfiguredApp") def preconfigured_app(self) -> pulumi.Output[Optional[str]]: """ name of application from the Okta Integration Network, if not included a custom app will be created. """ return pulumi.get(self, "preconfigured_app") @property @pulumi.getter def recipient(self) -> pulumi.Output[Optional[str]]: """ The location where the app may present the SAML assertion. """ return pulumi.get(self, "recipient") @property @pulumi.getter(name="requestCompressed") def request_compressed(self) -> pulumi.Output[Optional[bool]]: """ Denotes whether the request is compressed or not. """ return pulumi.get(self, "request_compressed") @property @pulumi.getter(name="responseSigned") def response_signed(self) -> pulumi.Output[Optional[bool]]: """ Determines whether the SAML auth response message is digitally signed. """ return pulumi.get(self, "response_signed") @property @pulumi.getter(name="samlVersion") def saml_version(self) -> pulumi.Output[Optional[str]]: """ SAML version for the app's sign-on mode. Valid values are: `"2.0"` or `"1.1"`. Default is `"2.0"`. """ return pulumi.get(self, "saml_version") @property @pulumi.getter(name="signOnMode") def sign_on_mode(self) -> pulumi.Output[str]: """ Sign-on mode of application. """ return pulumi.get(self, "sign_on_mode") @property @pulumi.getter(name="signatureAlgorithm") def signature_algorithm(self) -> pulumi.Output[Optional[str]]: """ Signature algorithm used ot digitally sign the assertion and response. """ return pulumi.get(self, "signature_algorithm") @property @pulumi.getter(name="singleLogoutCertificate") def single_logout_certificate(self) -> pulumi.Output[Optional[str]]: """ x509 encoded certificate that the Service Provider uses to sign Single Logout requests. Note: should be provided without `-----BEGIN CERTIFICATE-----` and `-----END CERTIFICATE-----`, see [official documentation](https://developer.okta.com/docs/reference/api/apps/#service-provider-certificate). """ return pulumi.get(self, "single_logout_certificate") @property @pulumi.getter(name="singleLogoutIssuer") def single_logout_issuer(self) -> pulumi.Output[Optional[str]]: """ The issuer of the Service Provider that generates the Single Logout request. """ return pulumi.get(self, "single_logout_issuer") @property @pulumi.getter(name="singleLogoutUrl") def single_logout_url(self) -> pulumi.Output[Optional[str]]: """ The location where the logout response is sent. """ return pulumi.get(self, "single_logout_url") @property @pulumi.getter(name="skipGroups") def skip_groups(self) -> pulumi.Output[Optional[bool]]: """ Indicator that allows the app to skip `groups` sync (it's also can be provided during import). Default is `false`. """ return pulumi.get(self, "skip_groups") @property @pulumi.getter(name="skipUsers") def skip_users(self) -> pulumi.Output[Optional[bool]]: """ Indicator that allows the app to skip `users` sync (it's also can be provided during import). Default is `false`. """ return pulumi.get(self, "skip_users") @property @pulumi.getter(name="spIssuer") def sp_issuer(self) -> pulumi.Output[Optional[str]]: """ SAML service provider issuer. """ return pulumi.get(self, "sp_issuer") @property @pulumi.getter(name="ssoUrl") def sso_url(self) -> pulumi.Output[Optional[str]]: """ Single Sign-on Url. """ return pulumi.get(self, "sso_url") @property @pulumi.getter def status(self) -> pulumi.Output[Optional[str]]: """ status of application. """ return pulumi.get(self, "status") @property @pulumi.getter(name="subjectNameIdFormat") def subject_name_id_format(self) -> pulumi.Output[Optional[str]]: """ Identifies the SAML processing rules. """ return pulumi.get(self, "subject_name_id_format") @property @pulumi.getter(name="subjectNameIdTemplate") def subject_name_id_template(self) -> pulumi.Output[Optional[str]]: """ Template for app user's username when a user is assigned to the app. """ return pulumi.get(self, "subject_name_id_template") @property @pulumi.getter(name="userNameTemplate") def user_name_template(self) -> pulumi.Output[Optional[str]]: """ Username template. """ return pulumi.get(self, "user_name_template") @property @pulumi.getter(name="userNameTemplateSuffix") def user_name_template_suffix(self) -> pulumi.Output[Optional[str]]: """ Username template suffix. """ return pulumi.get(self, "user_name_template_suffix") @property @pulumi.getter(name="userNameTemplateType") def user_name_template_type(self) -> pulumi.Output[Optional[str]]: """ Username template type. """ return pulumi.get(self, "user_name_template_type") @property @pulumi.getter def users(self) -> pulumi.Output[Optional[Sequence['outputs.SamlUser']]]: """ Users associated with the application. - `DEPRECATED`: Please replace usage with the `app.User` resource. """ return pulumi.get(self, "users")

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0.943838

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0.921745

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0.238531

137,085

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false

0.000614

0.0043

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1

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null

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f04b3f2e5b4f3b11cc74bc92b628eefc0e653bde

42,572

py

Python

src/beginners/layer1.py

lilyychen96/Cubr

83e05f612f259bcd93b8f2fb8c7149ddae09d85b

[ "MIT" ]

null

src/beginners/layer1.py

lilyychen96/Cubr

83e05f612f259bcd93b8f2fb8c7149ddae09d85b

[ "MIT" ]

null

src/beginners/layer1.py

lilyychen96/Cubr

83e05f612f259bcd93b8f2fb8c7149ddae09d85b

[ "MIT" ]

null

import sys, os sys.path.insert(0, os.path.abspath('src/cube')) from moves import execute_moves from cube import Cube, find_edge, find_corner from facelet import Color as Cl, Corner as Cn, Edge as Ed """ white cross: part 1 of first layer algorithms """ def is_white_cross(cube_state): """ Checks if the cube has reached the "white cross" state """ return ((cube_state[31] == Cl.D) and (cube_state[28] == Cl.D) and (cube_state[25] == Cl.F) and (cube_state[30] == Cl.D) and (cube_state[43] == Cl.L) and (cube_state[34] == Cl.D) and (cube_state[52] == Cl.B) and (cube_state[32] == Cl.D) and (cube_state[16] == Cl.R)) def move_DF(cube_obj, loc): """ Returns the moves list to orient and position the DF edge """ cb = cube_obj.get_cb() cubies = cube_obj.cubies if loc == Ed.UR: try: assert((cb[5] == Cl.D) or (cb[10] == Cl.D)) if (cb[5] == Cl.D): return ["R2", "D3"] else: # cb[10] == Cl.D) return ["R3", "F1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UR]) elif loc == Ed.UF: try: assert((cb[7] == Cl.D) or (cb[19] == Cl.D)) if (cb[7] == Cl.D): return ["F2"] else: # cb[19] == Cl.D) return ["U1", "L1", "F3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UF]) elif loc == Ed.UL: try: assert((cb[3] == Cl.D) or (cb[37] == Cl.D)) if (cb[3] == Cl.D): return ["L2", "D1"] else: # cb[37] == Cl.D) return ["L1", "F3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UL]) elif loc == Ed.UB: try: assert((cb[1] == Cl.D) or (cb[46] == Cl.D)) if (cb[1] == Cl.D): return ["B2", "D2"] else: # cb[46] == Cl.D) return ["U3", "L1", "F3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UB]) elif loc == Ed.DR: try: assert((cb[32] == Cl.D) or (cb[16] == Cl.D)) if (cb[32] == Cl.D): return ["D3"] else: # cb[16] == Cl.D) return ["R1", "F1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DR]) elif loc == Ed.DF: try: assert((cb[28] == Cl.D) or (cb[25] == Cl.D)) if ((cb[28] == Cl.F) and (cb[25] == Cl.D)): return ["F2", "U3", "R3", "F1"] else: assert((cb[28] == Cl.D) and (cb[25] == Cl.F)) return [] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DF]) elif loc == Ed.DL: try: assert((cb[30] == Cl.D) or (cb[43] == Cl.D)) if (cb[30] == Cl.D): return ["D1"] else: # cb[43] == Cl.D) return ["L3", "F3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DL]) elif loc == Ed.DB: try: assert((cb[34] == Cl.D) or (cb[52] == Cl.D)) if (cb[34] == Cl.D): return ["D2"] else: # cb[52] == Cl.D) return ["B1", "R1", "D3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DB]) elif loc == Ed.FR: try: assert((cb[23] == Cl.D) or (cb[12] == Cl.D)) if (cb[23] == Cl.D): return ["R3", "D3"] else: # cb[12] == Cl.D) return ["F1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.FR]) elif loc == Ed.FL: try: assert((cb[21] == Cl.D) or (cb[41] == Cl.D)) if (cb[21] == Cl.D): return ["L1", "D1"] else: # cb[41] == Cl.D) return ["F3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.FL]) elif loc == Ed.BR: try: assert((cb[14] == Cl.D) or (cb[48] == Cl.D)) if (cb[14] == Cl.D): return ["B3", "D2"] else: # cb[48] == Cl.D) return ["R1", "D3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.BR]) else: #if loc == Ed.BL try: assert((cb[39] == Cl.D) or (cb[50] == Cl.D)) if (cb[39] == Cl.D): return ["B1", "D2"] else: # cb[50] == Cl.D) return ["L3", "D1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.BL]) return [] def move_DL(cube_obj, loc): """ Returns the moves list to orient and position the DL edge """ cb = cube_obj.get_cb() cubies = cube_obj.cubies if loc == Ed.UR: try: assert((cb[5] == Cl.D) or (cb[10] == Cl.D)) if (cb[5] == Cl.D): return ["U2", "L2"] else: # cb[10] == Cl.D) return ["U3", "B1", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UR]) elif loc == Ed.UF: try: assert((cb[7] == Cl.D) or (cb[19] == Cl.D)) if (cb[7] == Cl.D): return ["U1", "L2"] else: # cb[19] == Cl.D) return ["U2", "B1", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UF]) elif loc == Ed.UL: try: assert((cb[3] == Cl.D) or (cb[37] == Cl.D)) if (cb[3] == Cl.D): return ["L2"] else: # cb[37] == Cl.D) return ["U1", "B1", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UL]) elif loc == Ed.UB: try: assert((cb[1] == Cl.D) or (cb[46] == Cl.D)) if (cb[1] == Cl.D): return ["U3", "L2"] else: # cb[46] == Cl.D) return ["B1", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UB]) elif loc == Ed.DR: try: assert((cb[32] == Cl.D) or (cb[16] == Cl.D)) if (cb[32] == Cl.D): return ["R3", "B2", "L3"] else: # cb[16] == Cl.D) return ["R2", "U3", "B1", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DR]) elif loc == Ed.DF: try: # should not reach here assert((cb[25] == Cl.F) and (cb[28] == Cl.D)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.B])), cubies[Ed.DF])) elif loc == Ed.DL: try: assert((cb[30] == Cl.D) or (cb[43] == Cl.D)) if ((cb[30] == Cl.L) and (cb[43] == Cl.D)): return ["L1", "B3", "U3", "L2"] else: assert((cb[30] == Cl.D) and (cb[43] == Cl.L)) return [] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DL]) elif loc == Ed.DB: try: assert((cb[34] == Cl.D) or (cb[52] == Cl.D)) if (cb[34] == Cl.D): return ["B2", "U3", "L2"] else: # cb[52] == Cl.D) return ["B3", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DB]) elif loc == Ed.FR: try: assert((cb[23] == Cl.D) or (cb[12] == Cl.D)) if (cb[23] == Cl.D): return ["R1", "U2", "L2"] else: # cb[12] == Cl.D) return ["R1", "U3", "B1", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.FR]) elif loc == Ed.FL: try: assert((cb[21] == Cl.D) or (cb[41] == Cl.D)) if (cb[21] == Cl.D): return ["L1"] else: # cb[41] == Cl.D) return ["L3", "U1", "B1", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.FL]) elif loc == Ed.BR: try: assert((cb[14] == Cl.D) or (cb[48] == Cl.D)) if (cb[14] == Cl.D): return ["B1", "U3", "L2"] else: # cb[48] == Cl.D) return ["B2", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.BR]) else: #if loc == Ed.BL try: assert((cb[39] == Cl.D) or (cb[50] == Cl.D)) if (cb[39] == Cl.D): return ["B3", "U3", "L2"] else: # cb[50] == Cl.D) return ["L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.BL]) return [] def move_DB(cube_obj, loc): """ Returns the moves list to orient and position the DB edge """ cb = cube_obj.get_cb() cubies = cube_obj.cubies if loc == Ed.UR: try: assert((cb[5] == Cl.D) or (cb[10] == Cl.D)) if (cb[5] == Cl.D): return ["U3", "B2"] else: # cb[10] == Cl.D) return ["R1", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UR]) elif loc == Ed.UF: try: assert((cb[7] == Cl.D) or (cb[19] == Cl.D)) if (cb[7] == Cl.D): return ["U2", "B2"] else: # cb[19] == Cl.D) return ["U3", "R1", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UF]) elif loc == Ed.UL: try: assert((cb[3] == Cl.D) or (cb[37] == Cl.D)) if (cb[3] == Cl.D): return ["U1", "B2"] else: # cb[37] == Cl.D) return ["U2", "R1", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UL]) elif loc == Ed.UB: try: assert((cb[1] == Cl.D) or (cb[46] == Cl.D)) if (cb[1] == Cl.D): return ["B2"] else: # cb[46] == Cl.D) return ["U1", "R1", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UB]) elif loc == Ed.DR: try: assert((cb[32] == Cl.D) or (cb[16] == Cl.D)) if (cb[32] == Cl.D): return ["R2", "U3", "B2"] else: # cb[16] == Cl.D) return ["R3", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DR]) elif loc == Ed.DF: try: # should not reach here assert((cb[25] == Cl.F) and (cb[28] == Cl.D)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.B])), cubies[Ed.DF])) elif loc == Ed.DL: try: # should not reach here assert((cb[30] == Cl.D) and (cb[43] == Cl.L)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.L])), cubies[Ed.DL])) elif loc == Ed.DB: try: assert((cb[34] == Cl.D) or (cb[52] == Cl.D)) if ((cb[34] == Cl.B) and (cb[52] == Cl.D)): return ["B2", "U1", "R1", "B3"] else: assert((cb[34] == Cl.D) and (cb[52] == Cl.B)) return [] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DL]) elif loc == Ed.FR: try: assert((cb[23] == Cl.D) or (cb[12] == Cl.D)) if (cb[23] == Cl.D): return ["R1", "U3", "B2"] else: # cb[12] == Cl.D) return ["R2", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.FR]) elif loc == Ed.FL: try: assert((cb[21] == Cl.D) or (cb[41] == Cl.D)) if (cb[21] == Cl.D): return ["D1", "L1", "D3"] else: # cb[41] == Cl.D) return ["D2", "F3", "D2"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.FL]) elif loc == Ed.BR: try: assert((cb[14] == Cl.D) or (cb[48] == Cl.D)) if (cb[14] == Cl.D): return ["B3"] else: # cb[48] == Cl.D) return ["B1", "U1", "R1", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.BR]) else: #if loc == Ed.BL try: assert((cb[39] == Cl.D) or (cb[50] == Cl.D)) if (cb[39] == Cl.D): return ["B1"] else: # cb[50] == Cl.D) return ["B3", "U1", "R1", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.BL]) return [] def move_DR(cube_obj, loc): """ Returns the moves list to orient and position the DR edge """ cb = cube_obj.get_cb() cubies = cube_obj.cubies if loc == Ed.UR: try: assert((cb[5] == Cl.D) or (cb[10] == Cl.D)) if (cb[5] == Cl.D): return ["R2"] else: # cb[10] == Cl.D) return ["R1", "D1", "B3", "D3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UR]) elif loc == Ed.UF: try: assert((cb[7] == Cl.D) or (cb[19] == Cl.D)) if (cb[7] == Cl.D): return ["U3", "R2"] else: # cb[19] == Cl.D) return ["U2", "B3", "R1", "B1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UF]) elif loc == Ed.UL: try: assert((cb[3] == Cl.D) or (cb[37] == Cl.D)) if (cb[3] == Cl.D): return ["U2", "R2"] else: # cb[37] == Cl.D) return ["U1", "B3", "R1", "B1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UL]) elif loc == Ed.UB: try: assert((cb[1] == Cl.D) or (cb[46] == Cl.D)) if (cb[1] == Cl.D): return ["U1", "R2"] else: # cb[46] == Cl.D) return ["B3", "R1", "B1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.UB]) elif loc == Ed.DR: try: assert((cb[32] == Cl.D) or (cb[16] == Cl.D)) if ((cb[32] == Cl.R) and (cb[16] == Cl.D)): return ["R3", "D1", "B3", "D3"] else: assert((cb[32] == Cl.D) and (cb[16] == Cl.R)) return [] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.DR]) elif loc == Ed.DF: try: # should not reach here assert((cb[25] == Cl.F) and (cb[28] == Cl.D)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.B])), cubies[Ed.DF])) elif loc == Ed.DL: try: # should not reach here assert((cb[30] == Cl.D) and (cb[43] == Cl.L)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.L])), cubies[Ed.DL])) elif loc == Ed.DB: try: # should not reach here assert((cb[34] == Cl.D) and (cb[52] == Cl.B)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.B])), cubies[Ed.DB])) elif loc == Ed.FR: try: assert((cb[23] == Cl.D) or (cb[12] == Cl.D)) if (cb[23] == Cl.D): return ["R3"] else: # cb[12] == Cl.D) return ["D3", "F1", "D1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.FR]) elif loc == Ed.FL: try: assert((cb[21] == Cl.D) or (cb[41] == Cl.D)) if (cb[21] == Cl.D): return ["D2", "L1", "D2"] else: # cb[41] == Cl.D) return ["D3", "F3", "D1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.FL]) elif loc == Ed.BR: try: assert((cb[14] == Cl.D) or (cb[48] == Cl.D)) if (cb[14] == Cl.D): return ["D1", "B3", "D3"] else: # cb[48] == Cl.D) return ["R1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.BR]) else: #if loc == Ed.BL try: assert((cb[39] == Cl.D) or (cb[50] == Cl.D)) if (cb[39] == Cl.D): return ["D1", "B1", "D3"] else: # cb[50] == Cl.D) return ["D2", "L3", "D2"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s)" % cubies[Ed.BL]) return [] def white_cross(cube_obj): """ Outputs the moves list for solving the down face edge cubies according to the initial cube state """ # search for cubies and move into place # edge DF cube_state = cube_obj.cb cubies = cube_obj.cubies if is_white_cross(cube_state): print("white cross completed") print(cube_obj) return # print("DF") # print(cube_obj) if not ((cube_state[28] == Cl.D) and (cube_state[25] == Cl.F)): loc = find_edge(cubies, tuple(sorted([Cl.D, Cl.F]))) # print(loc) if loc is None: print("can't find edge (%s, %s)" % tuple(sorted([Cl.D, Cl.F]))) else: move_list = move_DF(cube_obj, loc) execute_moves(cube_obj, move_list) # edge DL cube_state = cube_obj.cb cubies = cube_obj.cubies if is_white_cross(cube_state): print("white cross completed") print(cube_obj) return # print("DL") # print(cube_obj) if not ((cube_state[30] == Cl.D) and (cube_state[43] == Cl.L)): loc = find_edge(cubies, tuple(sorted([Cl.D, Cl.L]))) # print(loc) if loc is None: print("can't find edge (%s, %s)" % tuple(sorted([Cl.D, Cl.L]))) else: move_list = move_DL(cube_obj, loc) execute_moves(cube_obj, move_list) # edge DB cube_state = cube_obj.cb cubies = cube_obj.cubies if is_white_cross(cube_state): print("white cross completed") print(cube_obj) return # print("DB") # print(cube_obj) if not ((cube_state[34] == Cl.D) and (cube_state[52] == Cl.B)): loc = find_edge(cubies, tuple(sorted([Cl.D, Cl.B]))) # print(loc) if loc is None: print("can't find edge (%s, %s)" % tuple(sorted([Cl.D, Cl.B]))) else: move_list = move_DB(cube_obj, loc) execute_moves(cube_obj, move_list) # edge DR cube_state = cube_obj.cb cubies = cube_obj.cubies if is_white_cross(cube_state): print("white cross completed") print(cube_obj) return # print("DR") # print(cube_obj) if not ((cube_state[32] == Cl.D) and (cube_state[16] == Cl.R)): loc = find_edge(cubies, tuple(sorted([Cl.D, Cl.R]))) # print(loc) if loc is None: print("can't find edge (%s, %s)" % tuple(sorted([Cl.U, Cl.R]))) else: move_list = move_DR(cube_obj, loc) execute_moves(cube_obj, move_list) try: assert(is_white_cross(cube_obj.cb)) print("white cross completed") print(cube_obj) except AssertionError: print("did not successfully reach white cross state\n") """ white corners: part 2 of first layer algorithms """ def is_white_corners(cstate): """ Checks if the cube has reached the "white corners" state """ return (is_white_cross(cstate) and (cstate[29] == Cl.D) and (cstate[26] == Cl.F) and (cstate[15] == Cl.R) and (cstate[27] == Cl.D) and (cstate[44] == Cl.L) and (cstate[24] == Cl.F) and (cstate[33] == Cl.D) and (cstate[53] == Cl.B) and (cstate[42] == Cl.L) and (cstate[35] == Cl.D) and (cstate[17] == Cl.R) and (cstate[51] == Cl.B)) def move_DFR(cube_obj, loc): """ Returns the moves list to orient and position the DFR corner """ cb = cube_obj.get_cb() cubies = cube_obj.cubies if loc == Cn.URF: try: assert((cb[8] == Cl.D) or (cb[9] == Cl.D) or (cb[20] == Cl.D)) if (cb[8] == Cl.D): return ["R1", "U2", "R3", "U2", "F3", "U1", "F1"] elif (cb[9] == Cl.D): return ["R1", "U1", "R3"] else: # cb[20] == Cl.D) return ["F3", "U3", "F1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.URF]) elif loc == Cn.UFL: try: assert((cb[6] == Cl.D) or (cb[18] == Cl.D) or (cb[38] == Cl.D)) if (cb[6] == Cl.D): return ["R1", "U2", "R3", "U1", "R1", "U3", "R3"] elif (cb[18] == Cl.D): return ["U3", "R1", "U1", "R3"] else: # cb[38] == Cl.D) return ["R1", "U3", "R3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.UFL]) elif loc == Cn.ULB: try: assert((cb[0] == Cl.D) or (cb[36] == Cl.D) or (cb[47] == Cl.D)) if (cb[0] == Cl.D): return ["R1", "U1", "R3", "U1", "R1", "U3", "R3"] elif (cb[36] == Cl.D): return ["F3", "U2", "F1"] else: # cb[47] == Cl.D) return ["R1", "U2", "R3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.ULB]) elif loc == Cn.UBR: try: assert((cb[2] == Cl.D) or (cb[45] == Cl.D) or (cb[11] == Cl.D)) if (cb[2] == Cl.D): return ["U3", "R1", "U1", "R3", "U1", "R1", "U3", "R3"] elif (cb[45] == Cl.D): return ["F3", "U1", "F1"] else: # cb[11] == Cl.D) return ["U2", "R1", "U3", "R3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.UBR]) elif loc == Cn.DFR: try: assert((cb[29] == Cl.D) or (cb[26] == Cl.D) or (cb[15] == Cl.D)) if (cb[26] == Cl.D): return ["R1", "U3", "R3", "U1", "R1", "U3", "R3"] elif (cb[15] == Cl.D): return ["R1", "U1", "R3", "U2", "F3", "U1", "F1"] else: # cb[29] == Cl.D) assert((cb[29] == Cl.D) and (cb[26] == Cl.F) and (cb[15] == Cl.R)) return [] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DFR]) elif loc == Cn.DLF: try: assert((cb[27] == Cl.D) or (cb[44] == Cl.D) or (cb[24] == Cl.D)) if (cb[27] == Cl.D): return ["F1", "U1", "F3", "R1", "U2", "R3"] elif (cb[44] == Cl.D): return ["L3", "R1", "U3", "L1", "R3"] else: # cb[24] == Cl.D) return ["L3", "R1", "U2", "R3", "U1", "R1", "U3", "R3", "L1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DLF]) elif loc == Cn.DBL: try: assert((cb[33] == Cl.D) or (cb[53] == Cl.D) or (cb[42] == Cl.D)) if (cb[33] == Cl.D): return ["B3", "F3", "U2", "B1", "F1"] elif (cb[53] == Cl.D): return ["L1", "R1", "U1", "R3", "U1", "R1", "U3", "R3", "L3"] else: # cb[42] == Cl.D) return ["B3", "R1", "U1", "R3", "B1", "U1", "R1", "U3", "R3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DBL]) else: #if loc == Cn.DRB try: assert((cb[35] == Cl.D) or (cb[17] == Cl.D) or (cb[51] == Cl.D)) if (cb[35] == Cl.D): return ["B1", "U2", "B3", "R1", "U3", "R3"] elif (cb[17] == Cl.D): return ["R3", "U2", "R2", "U3", "R3"] else: # cb[51] == Cl.D) return ["F3", "B1", "U1", "B3", "F1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DRB]) return [] def move_DLF(cube_obj, loc): """ Returns the moves list to orient and position the DFR corner """ cb = cube_obj.get_cb() cubies = cube_obj.cubies if loc == Cn.URF: try: assert((cb[8] == Cl.D) or (cb[9] == Cl.D) or (cb[20] == Cl.D)) if (cb[8] == Cl.D): return ["L3", "U2", "L1", "U3", "L3", "U1", "L1"] elif (cb[9] == Cl.D): return ["L3", "U1", "L1"] else: # cb[20] == Cl.D) return ["U2", "F1", "U3", "F3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.URF]) elif loc == Cn.UFL: try: assert((cb[6] == Cl.D) or (cb[18] == Cl.D) or (cb[38] == Cl.D)) if (cb[6] == Cl.D): return ["U1", "F1", "U2", "F3", "U1", "F1", "U3", "F3"] elif (cb[18] == Cl.D): return ["U3", "L3", "U1", "L1"] else: # cb[38] == Cl.D) return ["L3", "U3", "L1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.UFL]) elif loc == Cn.ULB: try: assert((cb[0] == Cl.D) or (cb[36] == Cl.D) or (cb[47] == Cl.D)) if (cb[0] == Cl.D): return ["U1", "L3", "U3", "L1", "U3", "L3", "U1", "L1"] elif (cb[36] == Cl.D): return ["U2", "L3", "U1", "L1"] else: # cb[47] == Cl.D) return ["F1", "U3", "F3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.ULB]) elif loc == Cn.UBR: try: assert((cb[2] == Cl.D) or (cb[45] == Cl.D) or (cb[11] == Cl.D)) if (cb[2] == Cl.D): return ["L3", "U3", "L1", "U3", "L3", "U1", "L1"] elif (cb[45] == Cl.D): return ["L3", "U2", "L1"] else: # cb[11] == Cl.D) return ["U3", "F1", "U3", "F3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.UBR]) elif loc == Cn.DFR: try: assert((cb[29] == Cl.D) and (cb[26] == Cl.F) and (cb[15] == Cl.R)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.F, Cl.R])), cubies[Cn.DFR])) elif loc == Cn.DLF: try: assert((cb[27] == Cl.D) or (cb[44] == Cl.D) or (cb[24] == Cl.D)) if (cb[44] == Cl.D): return ["L3", "U2", "L1", "U3", "F1", "U3", "F3"] elif (cb[24] == Cl.D): return ["F1", "U1", "F3", "U3", "F1", "U1", "F3", "U3"] else: # cb[27] == Cl.D) assert((cb[27] == Cl.D) and (cb[44] == Cl.L) and (cb[24] == Cl.F)) return [] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DLF]) elif loc == Cn.DBL: try: assert((cb[33] == Cl.D) or (cb[53] == Cl.D) or (cb[42] == Cl.D)) if (cb[33] == Cl.D): return ["B3", "U2", "B1", "L3", "U1", "L1"] elif (cb[53] == Cl.D): return ["B3", "U2", "B1", "U2", "F1", "U3", "F3"] else: # cb[42] == Cl.D) return ["B3", "U1", "B1", "U2", "L3", "U1", "L1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DBL]) else: #if loc == Cn.DRB try: assert((cb[35] == Cl.D) or (cb[17] == Cl.D) or (cb[51] == Cl.D)) if (cb[35] == Cl.D): return ["B1", "U1", "B3", "U2", "F1", "U3", "F3"] elif (cb[17] == Cl.D): return ["B1", "U3", "B3", "F1", "U2", "F3"] else: # cb[51] == Cl.D) return ["B1", "U1", "L3", "U1", "B3", "L1"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DRB]) return [] def move_DBL(cube_obj, loc): """ Returns the moves list to orient and position the DFR corner """ cb = cube_obj.get_cb() cubies = cube_obj.cubies if loc == Cn.URF: try: assert((cb[8] == Cl.D) or (cb[9] == Cl.D) or (cb[20] == Cl.D)) if (cb[8] == Cl.D): return ["B3", "U3", "B1", "U3", "B3", "U1", "B1"] elif (cb[9] == Cl.D): return ["U1", "B3", "U1", "B1"] else: # cb[20] == Cl.D) return ["U3", "L1", "U3", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.URF]) elif loc == Cn.UFL: try: assert((cb[6] == Cl.D) or (cb[18] == Cl.D) or (cb[38] == Cl.D)) if (cb[6] == Cl.D): return ["B3", "U2", "B1", "U3", "B3", "U1", "B1"] elif (cb[18] == Cl.D): return ["B3", "U1", "B1"] else: # cb[38] == Cl.D) return ["U2", "L1", "U3", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.UFL]) elif loc == Cn.ULB: try: assert((cb[0] == Cl.D) or (cb[36] == Cl.D) or (cb[47] == Cl.D)) if (cb[0] == Cl.D): return ["B3", "U1", "B1", "L1", "U2", "L3"] elif (cb[36] == Cl.D): return ["U3", "B3", "U1", "B1"] else: # cb[47] == Cl.D) return ["U1", "L1", "U3", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.ULB]) elif loc == Cn.UBR: try: assert((cb[2] == Cl.D) or (cb[45] == Cl.D) or (cb[11] == Cl.D)) if (cb[2] == Cl.D): return ["R3", "B2", "R1", "B2", "R1"] elif (cb[45] == Cl.D): return ["U3", "L1", "U1", "L3"] else: # cb[11] == Cl.D) return ["L1", "U3", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.UBR]) elif loc == Cn.DFR: try: assert((cb[29] == Cl.D) and (cb[26] == Cl.F) and (cb[15] == Cl.R)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.F, Cl.R])), cubies[Cn.DFR])) elif loc == Cn.DLF: try: assert((cb[27] == Cl.D) and (cb[44] == Cl.L) and (cb[24] == Cl.F)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.L, Cl.F])), cubies[Cn.DLF])) elif loc == Cn.DBL: try: assert((cb[33] == Cl.D) or (cb[53] == Cl.D) or (cb[42] == Cl.D)) if (cb[53] == Cl.D): return ["B3", "U1", "B1", "U3", "B3", "U2", "B1", "U3", "B3", "U1", "B1"] elif (cb[42] == Cl.D): return ["B3", "U1", "B1", "U3", "B3", "U1", "B1"] else: # cb[33] == Cl.D) assert((cb[33] == Cl.D) and (cb[53] == Cl.B) and (cb[42] == Cl.L)) return [] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DBL]) else: #if loc == Cn.DRB try: assert((cb[35] == Cl.D) or (cb[17] == Cl.D) or (cb[51] == Cl.D)) if (cb[35] == Cl.D): return ["B1", "U3", "B3", "U2", "B3", "U1", "B1"] elif (cb[17] == Cl.D): return ["B1", "U3", "B3", "L1", "U3", "L3"] else: # cb[51] == Cl.D) return ["B1", "U3", "B3", "L1", "U2", "L3", "U1", "L1", "U3", "L3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DRB]) return [] def move_DRB(cube_obj, loc): """ Returns the moves list to orient and position the DFR corner """ cb = cube_obj.get_cb() cubies = cube_obj.cubies if loc == Cn.URF: try: assert((cb[8] == Cl.D) or (cb[9] == Cl.D) or (cb[20] == Cl.D)) if (cb[8] == Cl.D): return ["B1", "U2", "B3", "U1", "B1", "U3", "B3"] elif (cb[9] == Cl.D): return ["U2", "R3", "U1", "R1"] else: # cb[20] == Cl.D) return ["B1", "U3", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.URF]) elif loc == Cn.UFL: try: assert((cb[6] == Cl.D) or (cb[18] == Cl.D) or (cb[38] == Cl.D)) if (cb[6] == Cl.D): return ["B1", "U1", "B3", "U1", "B1", "U3", "B3"] elif (cb[18] == Cl.D): return ["U1", "R3", "U1", "R1"] else: # cb[38] == Cl.D) return ["B1", "U2", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.UFL]) elif loc == Cn.ULB: try: assert((cb[0] == Cl.D) or (cb[36] == Cl.D) or (cb[47] == Cl.D)) if (cb[0] == Cl.D): return ["R3", "U2", "R1", "U3", "R3", "U1", "R1"] elif (cb[36] == Cl.D): return ["R3", "U1", "R1"] else: # cb[47] == Cl.D) return ["U2", "B1", "U3", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.ULB]) elif loc == Cn.UBR: try: assert((cb[2] == Cl.D) or (cb[45] == Cl.D) or (cb[11] == Cl.D)) if (cb[2] == Cl.D): return ["U1", "B1", "U2", "B3", "U1", "B1", "U3", "B3"] elif (cb[45] == Cl.D): return ["U3", "R3", "U1", "R1"] else: # cb[11] == Cl.D) return ["U1", "B1", "U3", "B3"] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.UBR]) elif loc == Cn.DFR: try: assert((cb[29] == Cl.D) and (cb[26] == Cl.F) and (cb[15] == Cl.R)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.F, Cl.R])), cubies[Cn.DFR])) elif loc == Cn.DLF: try: assert((cb[27] == Cl.D) and (cb[44] == Cl.L) and (cb[24] == Cl.F)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.L, Cl.F])), cubies[Cn.DLF])) elif loc == Cn.DBL: try: assert((cb[33] == Cl.D) and (cb[53] == Cl.B) and (cb[42] == Cl.L)) return [] except AssertionError: print("should be (%s); is (%s)" % (tuple(sorted([Cl.D, Cl.B, Cl.L])), cubies[Cn.DBL])) else: #if loc == Cn.DRB try: assert((cb[35] == Cl.D) or (cb[17] == Cl.D) or (cb[51] == Cl.D)) if (cb[17] == Cl.D): return ["B1", "U3", "B3", "U1", "B1", "U3", "B3"] elif (cb[51] == Cl.D): return ["B1", "U1", "B3", "U2", "R3", "U1", "R1"] else: # cb[51] == Cl.D) assert((cb[35] == Cl.D) and (cb[17] == Cl.R) and (cb[51] == Cl.B)) return [] except AssertionError: print("invalid colors (at least one should be Cl.D): (%s, %s, %s)" % cubies[Cn.DRB]) return [] def white_corners(cube_obj): """ Outputs the moves list for solving the down face corner cubies after solving for the white cross """ # search for cubies and move into place # corner DFR cstate = cube_obj.cb cubies = cube_obj.cubies if is_white_corners(cstate): print("white corners completed") print(cube_obj) return # print("DFR") # print(cube_obj) if not ((cstate[29] == Cl.D) and (cstate[26] == Cl.F) and (cstate[15] == Cl.R)): loc = find_corner(cubies, tuple(sorted([Cl.D, Cl.F, Cl.R]))) # print(loc) if loc is None: print("can't find corner (%s, %s, %s)" % tuple(sorted([Cl.D, Cl.F, Cl.R]))) else: move_list = move_DFR(cube_obj, loc) execute_moves(cube_obj, move_list) # corner DLF cstate = cube_obj.cb cubies = cube_obj.cubies if is_white_corners(cstate): print("white corners completed") print(cube_obj) return # print("DLF") # print(cube_obj) if not ((cstate[27] == Cl.D) and (cstate[44] == Cl.L) and (cstate[24] == Cl.F)): loc = find_corner(cubies, tuple(sorted([Cl.D, Cl.L, Cl.F]))) # print(loc) if loc is None: print("can't find corner (%s, %s, %s)" % tuple(sorted([Cl.D, Cl.L, Cl.F]))) else: move_list = move_DLF(cube_obj, loc) execute_moves(cube_obj, move_list) # corner DBL cstate = cube_obj.cb cubies = cube_obj.cubies if is_white_corners(cstate): print("white corners completed") print(cube_obj) return # print("DBL") # print(cube_obj) if not ((cstate[33] == Cl.D) and (cstate[53] == Cl.B) and (cstate[42] == Cl.L)): loc = find_corner(cubies, tuple(sorted([Cl.D, Cl.B, Cl.L]))) # print(loc) if loc is None: print("can't find corner (%s, %s, %s)" % tuple(sorted([Cl.D, Cl.B, Cl.L]))) else: move_list = move_DBL(cube_obj, loc) execute_moves(cube_obj, move_list) # corner DRB cstate = cube_obj.cb cubies = cube_obj.cubies if is_white_corners(cstate): print("white corners completed") print(cube_obj) return # print("DRB") # print(cube_obj) if not ((cstate[35] == Cl.D) and (cstate[17] == Cl.R) and (cstate[51] == Cl.B)): loc = find_corner(cubies, tuple(sorted([Cl.D, Cl.R, Cl.B]))) # print(loc) if loc is None: print("can't find corner (%s, %s, %s)" % tuple(sorted([Cl.D, Cl.R, Cl.B]))) else: move_list = move_DRB(cube_obj, loc) execute_moves(cube_obj, move_list) try: assert(is_white_corners(cube_obj.cb)) print("white corners completed") print(cube_obj) except AssertionError: print("did not successfully reach white corners state\n") def layer1(cube_obj): """ Calls the solving algorithms for the first layer: white cross and white corners """ white_cross(cube_obj) white_corners(cube_obj)

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null

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f04f7a6f7bce03ac21ae08e0c3f1d3e1acb13396

72

py

Python

models/__init__.py

fenghansen/ELD

39846c79b5bcb406881c52700d282a9c1149666e

[ "MIT" ]

258

2020-05-16T17:43:13.000Z

2022-03-22T07:02:54.000Z

models/__init__.py

scott-mao/ELD

c1e009f21ab7ac6e87c4e37588bee3856160cd93

[ "MIT" ]

23

2020-06-22T02:07:04.000Z

2022-03-25T01:33:20.000Z

models/__init__.py

scott-mao/ELD

c1e009f21ab7ac6e87c4e37588bee3856160cd93

[ "MIT" ]

39

2020-05-19T06:29:28.000Z

2022-03-21T04:00:16.000Z

from .ELD_model import ELDModel def eld_model(): return ELDModel()

14.4

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0.180556

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null

0

1

0

1

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7

f05ed14da55b2f34e53ec01aab443e19ae22d904

2,310

py

Python

train_step.py

terrifyzhao/multi_task_lm

b60bfe34a02e5483540062074b24135753c537cd

[ "Apache-2.0" ]

1

2022-02-16T06:34:16.000Z

train_step.py

terrifyzhao/multi_task_lm

b60bfe34a02e5483540062074b24135753c537cd

[ "Apache-2.0" ]

null

train_step.py

terrifyzhao/multi_task_lm

b60bfe34a02e5483540062074b24135753c537cd

[ "Apache-2.0" ]

null

import torch from annlp import get_device device = get_device() def base_step(batch, optim, model, amp): all_loss = 0 for index in range(len(batch)): optim.zero_grad() output = model(batch[index]['input_ids'].to(device), batch[index]['attention_mask'].to(device), labels=batch[index]['labels'].to(device), task_id=index) loss = output.loss all_loss += loss.item() if torch.cuda.is_available(): with amp.scale_loss(loss, optim) as scaled_loss: scaled_loss.backward() else: loss.backward() optim.step() return all_loss / len(batch) def weight_step(batch, optim, model, amp): all_loss = 0 for index in range(len(batch)): optim.zero_grad() output = model(batch[index]['input_ids'].to(device), batch[index]['attention_mask'].to(device), labels=batch[index]['labels'].to(device), task_id=index) loss = output.loss loss = torch.log(loss) all_loss += loss.item() if torch.cuda.is_available(): with amp.scale_loss(loss, optim) as scaled_loss: scaled_loss.backward() else: loss.backward() optim.step() return all_loss / len(batch) def grad_accumulation_step(batch, optim, model, amp, with_log=False): all_loss = None optim.zero_grad() for index in range(len(batch)): output = model(batch[index]['input_ids'].to(device), batch[index]['attention_mask'].to(device), labels=batch[index]['labels'].to(device), task_id=index) loss = output.loss if all_loss: if with_log: all_loss += torch.log(loss) else: all_loss += loss else: if with_log: all_loss = torch.log(loss) else: all_loss = loss if torch.cuda.is_available(): with amp.scale_loss(loss, optim) as scaled_loss: scaled_loss.backward() else: loss.backward() optim.step() return all_loss.item() / len(batch)

30

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271

2,310

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0.037131

0.048101

0.87173

0.853165

0.833755

0

0.001337

0.352381

2,310

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null

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1

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1

0

null

0

7

b2c6d6d88248f183e4c0bf30c74c2447e06ab738

194

py

Python

rbact/peewee/__init__.py

chin-wag/async-rbac

442b5d02ee785ba4d9c04d5cbb3afeeec6dac633

[ "MIT" ]

null

rbact/peewee/__init__.py

chin-wag/async-rbac

442b5d02ee785ba4d9c04d5cbb3afeeec6dac633

[ "MIT" ]

11

2021-11-29T14:43:05.000Z

2022-02-03T15:33:48.000Z

rbact/peewee/__init__.py

chin-wag/rbact

442b5d02ee785ba4d9c04d5cbb3afeeec6dac633

[ "MIT" ]

null

from .models import ModelsLoader, Users, Roles, UsersRoles, Rules from .peewee_adapter import PeeweeAdapter __all__ = ["PeeweeAdapter", "ModelsLoader", "Users", "Roles", "UsersRoles", "Rules"]

38.8

84

0.757732

20

194

7.1

0.6

0.239437

0.309859

0.450704

0.521127

0

0.108247

194

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null

0

1

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7

b2ede2e020a36b7f068328ab82a52d80d930da11

2,719

py

Python

src/Python/Unittests/test_read_write_stl.py

rzoller/OpenMesh

f84bca0b26c61eab5f9335b2191962ca8545c5f6

[ "BSD-3-Clause" ]

19

2020-08-13T05:15:09.000Z

2022-03-31T14:51:29.000Z

src/Python/Unittests/test_read_write_stl.py

ccopsey/OpenMesh

93e6e626c3f282bf4275521c33cd8da1ca559c7d

[ "BSD-3-Clause" ]

2

2020-09-08T07:03:04.000Z

2021-08-04T05:43:27.000Z

src/Python/Unittests/test_read_write_stl.py

ccopsey/OpenMesh

93e6e626c3f282bf4275521c33cd8da1ca559c7d

[ "BSD-3-Clause" ]

10

2020-08-06T02:37:46.000Z

2021-07-01T09:12:06.000Z

import unittest import openmesh class ReadWriteSTL(unittest.TestCase): def setUp(self): self.mesh = openmesh.TriMesh() def test_load_simple_stl_file(self): ok = openmesh.read_mesh(self.mesh, "cube1.stl") self.assertTrue(ok) self.assertEqual(self.mesh.n_vertices(), 7526) self.assertEqual(self.mesh.n_edges(), 22572) self.assertEqual(self.mesh.n_faces(), 15048) def test_load_simple_stl_file_with_normals(self): self.mesh.request_face_normals() options = openmesh.Options() options += openmesh.Options.FaceNormal ok = openmesh.read_mesh(self.mesh, "cube1.stl", options) self.assertTrue(ok) self.assertAlmostEqual(self.mesh.normal(self.mesh.face_handle(0))[0], -0.038545) self.assertAlmostEqual(self.mesh.normal(self.mesh.face_handle(0))[1], -0.004330) self.assertAlmostEqual(self.mesh.normal(self.mesh.face_handle(0))[2], 0.999247) self.assertEqual(self.mesh.n_vertices(), 7526) self.assertEqual(self.mesh.n_edges(), 22572) self.assertEqual(self.mesh.n_faces(), 15048) self.mesh.release_face_normals() def test_load_simple_stl_binary_file(self): ok = openmesh.read_mesh(self.mesh, "cube1Binary.stl") self.assertTrue(ok) self.assertEqual(self.mesh.n_vertices(), 7526) self.assertEqual(self.mesh.n_edges(), 22572) self.assertEqual(self.mesh.n_faces(), 15048) def test_load_simple_stl_binary_file_with_normals(self): self.mesh.request_face_normals() options = openmesh.Options() options += openmesh.Options.FaceNormal options += openmesh.Options.Binary ok = openmesh.read_mesh(self.mesh, "cube1Binary.stl", options) self.assertTrue(ok) self.assertTrue(options.is_binary()) self.assertTrue(options.face_has_normal()) self.assertFalse(options.vertex_has_normal()) self.assertAlmostEqual(self.mesh.normal(self.mesh.face_handle(0))[0], -0.038545, 5) self.assertAlmostEqual(self.mesh.normal(self.mesh.face_handle(0))[1], -0.004330, 5) self.assertAlmostEqual(self.mesh.normal(self.mesh.face_handle(0))[2], 0.999247, 5) self.assertEqual(self.mesh.n_vertices(), 7526) self.assertEqual(self.mesh.n_edges(), 22572) self.assertEqual(self.mesh.n_faces(), 15048) self.mesh.release_face_normals() if __name__ == '__main__': suite = unittest.TestLoader().loadTestsFromTestCase(ReadWriteSTL) unittest.TextTestRunner(verbosity=2).run(suite)

35.776316

91

0.650975

329

2,719

5.182371

0.182371

0.154839

0.133724

0.161877

0.808211

0.767155

0.748387

0.655718

0

0.055924

0.223979

2,719

75

92

36.253333

0.752133

0

0.48

0

0.020596

0

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false

0

0.04

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0.16

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null

0

1

0

1

0

null

0

1

0

7

650e1955fcc19edb16dd0fbf4dc28656ca2335df

99,470

py

Python

shenfun/legendre/bases.py

jaisw7/shenfun

7482beb5b35580bc45f72704b69343cc6fc1d773

[ "BSD-2-Clause" ]

1

2021-03-06T09:29:39.000Z

shenfun/legendre/bases.py

jaisw7/shenfun

7482beb5b35580bc45f72704b69343cc6fc1d773

[ "BSD-2-Clause" ]

null

shenfun/legendre/bases.py

jaisw7/shenfun

7482beb5b35580bc45f72704b69343cc6fc1d773

[ "BSD-2-Clause" ]

null

""" Module for defining function spaces in the Legendre family """ from __future__ import division import os import functools import sympy import numpy as np from numpy.polynomial import legendre as leg from scipy.special import eval_legendre from mpi4py_fft import fftw from shenfun.spectralbase import SpectralBase, work, Transform, islicedict, \ slicedict from .lobatto import legendre_lobatto_nodes_and_weights __all__ = ['LegendreBase', 'Orthogonal', 'ShenDirichlet', 'ShenBiharmonic', 'ShenNeumann', 'ShenBiPolar', 'ShenBiPolar0', 'NeumannDirichlet', 'DirichletNeumann', 'UpperDirichletNeumann', 'UpperDirichlet', 'BCDirichlet', 'BCBiharmonic', 'BCNeumann'] #pylint: disable=method-hidden,no-else-return,not-callable,abstract-method,no-member,cyclic-import try: import quadpy from mpmath import mp mp.dps = 30 has_quadpy = True except: has_quadpy = False mp = None mode = os.environ.get('SHENFUN_LEGENDRE_MODE', 'numpy') mode = mode if has_quadpy else 'numpy' class LegendreBase(SpectralBase): """Base class for all Legendre spaces Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto domain : 2-tuple of floats, optional The computational domain padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", domain=(-1., 1.), dtype=np.float, padding_factor=1, dealias_direct=False, coordinates=None): SpectralBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) self.forward = functools.partial(self.forward, fast_transform=False) self.backward = functools.partial(self.backward, fast_transform=False) self.scalar_product = functools.partial(self.scalar_product, fast_transform=False) self.plan(int(padding_factor*N), 0, dtype, {}) @staticmethod def family(): return 'legendre' def reference_domain(self): return (-1, 1) def points_and_weights(self, N=None, map_true_domain=False, weighted=True, **kw): if N is None: N = self.shape(False) if self.quad == "LG": points, weights = leg.leggauss(N) elif self.quad == "GL": points, weights = legendre_lobatto_nodes_and_weights(N) else: raise NotImplementedError if map_true_domain is True: points = self.map_true_domain(points) return points, weights def mpmath_points_and_weights(self, N=None, map_true_domain=False, weighted=True, **kw): if mode == 'numpy' or not has_quadpy: return self.points_and_weights(N=N, map_true_domain=map_true_domain, weighted=weighted, **kw) if N is None: N = self.shape(False) if self.quad == 'LG': pw = quadpy.line_segment.gauss_legendre(N, 'mpmath') elif self.quad == 'GL': pw = quadpy.line_segment.gauss_lobatto(N) # No mpmath in quadpy for lobatto:-( points = pw.points if map_true_domain is True: points = self.map_true_domain(points) return points, pw.weights def vandermonde(self, x): return leg.legvander(x, self.shape(False)-1) def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): return sympy.legendre(i, x) def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) output_array = eval_legendre(i, x, out=output_array) return output_array def evaluate_basis_derivative_all(self, x=None, k=0, argument=0): if x is None: x = self.mesh(False, False) V = self.vandermonde(x) #N, M = self.shape(False), self.shape(True) M = V.shape[-1] if k > 0: D = np.zeros((M, M)) D[:-k] = leg.legder(np.eye(M, M), k) V = np.dot(V, D) return self._composite(V, argument=argument) def evaluate_basis_all(self, x=None, argument=0): if x is None: x = self.mesh(False, False) V = self.vandermonde(x) return self._composite(V, argument=argument) def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) x = np.atleast_1d(x) basis = np.zeros(self.shape(True)) basis[i] = 1 basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) return basis(x) def _composite(self, V, argument=0): """Return composite basis, where ``V`` is primary Vandermonde matrix.""" return V def plan(self, shape, axis, dtype, options): if shape in (0, (0,)): return if isinstance(axis, tuple): assert len(axis) == 1 axis = axis[0] if isinstance(self.forward, Transform): if self.forward.input_array.shape == shape and self.axis == axis: # Already planned return U = fftw.aligned(shape, dtype=dtype) V = fftw.aligned(shape, dtype=dtype) U.fill(0) V.fill(0) self.axis = axis if self.padding_factor > 1.+1e-8: trunc_array = self._get_truncarray(shape, V.dtype) self.forward = Transform(self.forward, None, U, V, trunc_array) self.backward = Transform(self.backward, None, trunc_array, V, U) else: self.forward = Transform(self.forward, None, U, V, V) self.backward = Transform(self.backward, None, V, V, U) self.scalar_product = Transform(self.scalar_product, None, U, V, V) self.si = islicedict(axis=self.axis, dimensions=self.dimensions) self.sl = slicedict(axis=self.axis, dimensions=self.dimensions) def get_orthogonal(self): return Orthogonal(self.N, quad=self.quad, dtype=self.dtype, domain=self.domain, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates) class Orthogonal(LegendreBase): """Function space for regular (orthogonal) Legendre series Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto domain : 2-tuple of floats, optional The computational domain padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", domain=(-1., 1.), dtype=np.float, padding_factor=1, dealias_direct=False, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) def eval(self, x, u, output_array=None): if output_array is None: output_array = np.zeros(x.shape, dtype=self.dtype) x = self.map_reference_domain(x) output_array[:] = leg.legval(x, u) return output_array @property def is_orthogonal(self): return True class ShenDirichlet(LegendreBase): """Legendre Function space for Dirichlet boundary conditions Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto bc : tuple of numbers Boundary conditions at edges of domain domain : 2-tuple of floats, optional The computational domain scaled : bool, optional Whether or not to scale test functions with 1/sqrt(4k+6). Scaled test functions give a stiffness matrix equal to the identity matrix. padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", bc=(0., 0.), domain=(-1., 1.), dtype=np.float, scaled=False, padding_factor=1, dealias_direct=False, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) from shenfun.tensorproductspace import BoundaryValues self._scaled = scaled self._factor = np.ones(1) self._bc_basis = None self.bc = BoundaryValues(self, bc=bc) @staticmethod def boundary_condition(): return 'Dirichlet' @property def has_nonhomogeneous_bcs(self): return self.bc.has_nonhomogeneous_bcs() def set_factor_array(self, v): if self.is_scaled(): if not self._factor.shape == v.shape: k = self.wavenumbers().astype(np.float) self._factor = 1./np.sqrt(4*k+6) def is_scaled(self): return self._scaled def _composite(self, V, argument=0): P = np.zeros(V.shape) if not self.is_scaled(): P[:, :-2] = V[:, :-2] - V[:, 2:] else: k = np.arange(self.N-2).astype(np.float) P[:, :-2] = (V[:, :-2] - V[:, 2:])/np.sqrt(4*k+6) if argument == 1: P[:, -2] = (V[:, 0] - V[:, 1])/2 P[:, -1] = (V[:, 0] + V[:, 1])/2 return P def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = np.zeros_like(input_array) else: output_array.fill(0) s0 = self.sl[slice(0, -2)] s1 = self.sl[slice(2, None)] if self.is_scaled(): k = self.wavenumbers() output_array[s0] = input_array[s0]/np.sqrt(4*k+6) output_array[s1] -= input_array[s0]/np.sqrt(4*k+6) else: output_array[s0] = input_array[s0] output_array[s1] -= input_array[s0] self.bc.add_to_orthogonal(output_array, input_array) return output_array def slice(self): return slice(0, self.N-2) def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): f = sympy.legendre(i, x)-sympy.legendre(i+2, x) if self.is_scaled(): f /= np.sqrt(4*i+6) return f def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) output_array[:] = eval_legendre(i, x) - eval_legendre(i+2, x) if self.is_scaled(): output_array /= np.sqrt(4*i+6) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) if output_array is None: output_array = np.zeros(x.shape) x = np.atleast_1d(x) basis = np.zeros(self.shape(True)) basis[np.array([i, i+2])] = (1, -1) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) if self.is_scaled(): output_array /= np.sqrt(4*i+6) return output_array def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.si[-2]] = 0 self.scalar_product.output_array[self.si[-1]] = 0 def eval(self, x, u, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape, dtype=self.dtype) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] self.set_factor_array(u) output_array[:] = leg.legval(x, u[:-2]*self._factor) w_hat[2:] = u[:-2]*self._factor output_array -= leg.legval(x, w_hat) output_array += 0.5*(u[-1]*(1+x) + u[-2]*(1-x)) return output_array def get_bc_basis(self): if self._bc_basis: return self._bc_basis self._bc_basis = BCDirichlet(self.N, quad=self.quad, domain=self.domain, scaled=self._scaled, coordinates=self.coors.coordinates) return self._bc_basis def get_refined(self, N): return ShenDirichlet(N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc, scaled=self._scaled) def get_dealiased(self, padding_factor=1.5, dealias_direct=False): return ShenDirichlet(self.N, quad=self.quad, dtype=self.dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, domain=self.domain, coordinates=self.coors.coordinates, bc=self.bc.bc, scaled=self._scaled) def get_unplanned(self): return ShenDirichlet(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc, scaled=self._scaled) class ShenNeumann(LegendreBase): """Function space for homogeneous Neumann boundary conditions Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto mean : number mean value bc : 2-tuple of numbers Boundary conditions at edges of domain domain : 2-tuple of floats, optional The computational domain padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", mean=0, bc=(0., 0.), domain=(-1., 1.), padding_factor=1, dealias_direct=False, dtype=np.float, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) from shenfun.tensorproductspace import BoundaryValues self.mean = mean self._factor = np.zeros(0) self._bc_basis = None self.bc = BoundaryValues(self, bc=bc) @staticmethod def boundary_condition(): return 'Neumann' @property def has_nonhomogeneous_bcs(self): return self.bc.has_nonhomogeneous_bcs() def _composite(self, V, argument=0): P = np.zeros(V.shape) k = np.arange(V.shape[1]).astype(np.float) P[:, :-2] = V[:, :-2] - (k[:-2]*(k[:-2]+1)/(k[:-2]+2))/(k[:-2]+3)*V[:, 2:] if argument == 1: P[:, -2] = 0.5*V[:, 1] - 1/6*V[:, 2] P[:, -1] = 0.5*V[:, 1] + 1/6*V[:, 2] return P def set_factor_array(self, v): if not self._factor.shape == v.shape: k = self.wavenumbers().astype(np.float) self._factor = k*(k+1)/(k+2)/(k+3) def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.sl[slice(-2, None)]] = 0 self.scalar_product.output_array[self.si[0]] = self.mean*np.pi def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): f = sympy.legendre(i, x) - (i*(i+1))/((i+2)*(i+3))*sympy.legendre(i+2, x) return f def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) output_array[:] = eval_legendre(i, x) - i*(i+1.)/(i+2.)/(i+3.)*eval_legendre(i+2, x) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) if output_array is None: output_array = np.zeros(x.shape) x = np.atleast_1d(x) basis = np.zeros(self.shape(True)) basis[np.array([i, i+2])] = (1, -i*(i+1.)/(i+2.)/(i+3.)) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) return output_array def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = np.zeros_like(input_array) else: output_array.fill(0) s0 = self.sl[slice(0, -2)] s1 = self.sl[slice(2, None)] self.set_factor_array(input_array) output_array[s0] = input_array[s0] output_array[s1] -= self._factor*input_array[s0] self.bc.add_to_orthogonal(output_array, input_array) return output_array def slice(self): return slice(0, self.N-2) def eval(self, x, u, output_array=None): if output_array is None: output_array = np.zeros(x.shape, dtype=self.dtype) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] self.set_factor_array(u) output_array[:] = leg.legval(x, u[:-2]) w_hat[2:] = self._factor*u[:-2] output_array -= leg.legval(x, w_hat) output_array += u[-2]*(0.5*x-1/3*(3*x**2-1)) + u[-1]*(0.5*x+1/3*(3*x**2-1)) return output_array def get_bc_basis(self): if self._bc_basis: return self._bc_basis self._bc_basis = BCNeumann(self.N, quad=self.quad, domain=self.domain, coordinates=self.coors.coordinates) return self._bc_basis def get_refined(self, N): return ShenNeumann(N, quad=self.quad, domain=self.domain, bc=self.bc.bc, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, mean=self.mean) def get_dealiased(self, padding_factor=1.5, dealias_direct=False): return ShenNeumann(self.N, quad=self.quad, domain=self.domain, bc=self.bc.bc, dtype=self.dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=self.coors.coordinates, mean=self.mean) def get_unplanned(self): return ShenNeumann(self.N, quad=self.quad, domain=self.domain, bc=self.bc.bc, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, mean=self.mean) class ShenBiharmonic(LegendreBase): """Function space for biharmonic basis Both Dirichlet and Neumann boundary conditions. Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto 4-tuple of numbers, optional The values of the 4 boundary conditions at x=(-1, 1). The two Dirichlet first and then the Neumann. domain : 2-tuple of floats, optional The computational domain padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", bc=(0, 0, 0, 0), domain=(-1., 1.), padding_factor=1, dealias_direct=False, dtype=np.float, coordinates=None): from shenfun.tensorproductspace import BoundaryValues LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) self._factor1 = np.zeros(0) self._factor2 = np.zeros(0) self._bc_basis = None self.bc = BoundaryValues(self, bc=bc) @staticmethod def boundary_condition(): return 'Biharmonic' @property def has_nonhomogeneous_bcs(self): return self.bc.has_nonhomogeneous_bcs() def _composite(self, V, argument=0): P = np.zeros_like(V) k = np.arange(V.shape[1]).astype(np.float)[:-4] P[:, :-4] = V[:, :-4] - (2*(2*k+5)/(2*k+7))*V[:, 2:-2] + ((2*k+3)/(2*k+7))*V[:, 4:] if argument == 1: P[:, -4:] = np.tensordot(V[:, :4], BCBiharmonic.coefficient_matrix(), (1, 1)) return P def set_factor_arrays(self, v): s = self.sl[self.slice()] if not self._factor1.shape == v[s].shape: k = self.wavenumbers().astype(np.float) self._factor1 = (-2*(2*k+5)/(2*k+7)).astype(float) self._factor2 = ((2*k+3)/(2*k+7)).astype(float) def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.sl[slice(-4, None)]] = 0 #@optimizer def set_w_hat(self, w_hat, fk, f1, f2): # pragma: no cover s = self.sl[self.slice()] s2 = self.sl[slice(2, -2)] s4 = self.sl[slice(4, None)] w_hat[s] = fk[s] w_hat[s2] += f1*fk[s] w_hat[s4] += f2*fk[s] return w_hat def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i < self.N-4: f = (sympy.legendre(i, x) -2*(2*i+5.)/(2*i+7.)*sympy.legendre(i+2, x) +((2*i+3.)/(2*i+7.))*sympy.legendre(i+4, x)) else: f = 0 for j, c in enumerate(BCBiharmonic.coefficient_matrix()[i-(self.N-4)]): f += c*sympy.legendre(j, x) return f def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i < self.N-4: output_array[:] = eval_legendre(i, x) - 2*(2*i+5.)/(2*i+7.)*eval_legendre(i+2, x) + ((2*i+3.)/(2*i+7.))*eval_legendre(i+4, x) else: X = sympy.symbols('x', real=True) output_array[:] = sympy.lambdify(X, self.sympy_basis(i, x=X))(x) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) if output_array is None: output_array = np.zeros(x.shape) x = np.atleast_1d(x) if i < self.N-4: basis = np.zeros(self.shape(True)) basis[np.array([i, i+2, i+4])] = (1, -2*(2*i+5.)/(2*i+7.), ((2*i+3.)/(2*i+7.))) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) else: X = sympy.symbols('x', real=True) output_array[:] = sympy.lambdify(X, self.sympy_basis(i, X).diff(X, k))(x) return output_array def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = np.zeros_like(input_array) else: output_array.fill(0) self.set_factor_arrays(input_array) output_array = self.set_w_hat(output_array, input_array, self._factor1, self._factor2) self.bc.add_to_orthogonal(output_array, input_array) return output_array def slice(self): return slice(0, self.N-4) def eval(self, x, u, output_array=None): if output_array is None: output_array = np.zeros(x.shape, dtype=self.dtype) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] self.set_factor_arrays(u) output_array[:] = leg.legval(x, u[:-4]) w_hat[2:-2] = self._factor1*u[:-4] output_array += leg.legval(x, w_hat[:-2]) w_hat[4:] = self._factor2*u[:-4] w_hat[:4] = 0 output_array += leg.legval(x, w_hat) return output_array def get_bc_basis(self): if self._bc_basis: return self._bc_basis self._bc_basis = BCBiharmonic(self.N, quad=self.quad, domain=self.domain, coordinates=self.coors.coordinates) return self._bc_basis def get_refined(self, N): return ShenBiharmonic(N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_dealiased(self, padding_factor=1.5, dealias_direct=False): return ShenBiharmonic(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_unplanned(self): return ShenBiharmonic(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) class BeamFixedFree(LegendreBase): """Function space for biharmonic basis Function space for biharmonic basis Fulfills the following boundary conditions: u(-1) = a, u'(-1) = b, u''(1) = c, u'''(1) = d. Both Dirichlet and Neumann boundary conditions. Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto 4-tuple of numbers, optional The values of the 4 boundary conditions u(-1) = a, u'(-1) = b, u''(1) = c, u'''(1) = d domain : 2-tuple of floats, optional The computational domain padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbol('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", bc=(0, 0, 0, 0), domain=(-1., 1.), padding_factor=1, dealias_direct=False, dtype=np.float, coordinates=None): from shenfun.tensorproductspace import BoundaryValues LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) self._factor1 = np.zeros(0) self._factor2 = np.zeros(0) self._factor3 = np.zeros(0) self._factor4 = np.zeros(0) self._bc_basis = None self.bc = BoundaryValues(self, bc=bc) @staticmethod def boundary_condition(): return 'BeamFixedFree' @property def has_nonhomogeneous_bcs(self): return self.bc.has_nonhomogeneous_bcs() def _composite(self, V, argument=0): P = np.zeros_like(V) k = np.arange(V.shape[1]).astype(np.float)[:-4] P[:, :-4] = (V[:, :-4] + 4*(2*k+3)/((k+3)**2)*V[:, 1:-3] - 2*(k-1)*(k+1)*(k+6)*(2*k+5)/((k+3)**2*(k+4)*(2*k+7))*V[:, 2:-2] - 4*(k+1)**2*(2*k+3)/((k+3)**2*(k+4)**2)*V[:, 3:-1] + ((k+1)**2*(k+2)**2*(2*k+3)/((k+3)**2*(k+4)**2*(2*k+7)))*V[:, 4:]) if argument == 1: P[:, -4:] = np.tensordot(V[:, :4], BCBeamFixedFree.coefficient_matrix(), (1, 1)) return P def set_factor_arrays(self, v): s = self.sl[self.slice()] if not self._factor1.shape == v[s].shape: k = self.wavenumbers().astype(np.float) self._factor1 = (4*(2*k+3)/((k+3)**2)).astype(float) self._factor2 = (-(2*(k-1)*(k+1)*(k+6)*(2*k+5)/((k+3)**2*(k+4)*(2*k+7)))).astype(float) self._factor3 = (- 4*(k+1)**2*(2*k+3)/((k+3)**2*(k+4)**2)).astype(float) self._factor4 = ((((k+1)/(k+3))*((k+2)/(k+4)))**2*(2*k+3)/(2*k+7)).astype(float) def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.sl[slice(-4, None)]] = 0 def set_w_hat(self, w_hat, fk, f1, f2): # pragma: no cover s = self.sl[self.slice()] s2 = self.sl[slice(2, -2)] s4 = self.sl[slice(4, None)] w_hat[s] = fk[s] w_hat[s2] += f1*fk[s] w_hat[s4] += f2*fk[s] return w_hat def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i < self.N-4: f = (sympy.legendre(i, x) +(4*(2*i+3)/((i+3)**2))*sympy.legendre(i+1, x) -(2*(i-1)*(i+1)*(i+6)*(2*i+5)/((i+3)**2*(i+4)*(2*i+7)))*sympy.legendre(i+2, x) -4*(i+1)**2*(2*i+3)/((i+3)**2*(i+4)**2)*sympy.legendre(i+3, x) +(i+1)**2*(i+2)**2*(2*i+3)/((i+3)**2*(i+4)**2*(2*i+7))*sympy.legendre(i+4, x)) else: f = 0 for j, c in enumerate(BCBeamFixedFree.coefficient_matrix()[i-(self.N-4)]): f += c*sympy.legendre(j, x) return f def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i < self.N-4: output_array[:] = eval_legendre(i, x) + (4*(2*i+3)/((i+3)**2))*eval_legendre(i+1, x) \ -(2*(i-1)*(i+1)*(i+6)*(2*i+5)/((i+3)**2*(i+4)*(2*i+7)))*eval_legendre(i+2, x) \ -4*(i+1)**2*(2*i+3)/((i+3)**2*(i+4)**2)*eval_legendre(i+3, x) \ +(i+1)**2*(i+2)**2*(2*i+3)/((i+3)^2*(i+4)**2*(2*i+7))*eval_legendre(i+4, x) else: X = sympy.symbols('x', real=True) output_array[:] = sympy.lambdify(X, self.sympy_basis(i, x=X))(x) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) if output_array is None: output_array = np.zeros(x.shape) x = np.atleast_1d(x) if i < self.N-4: basis = np.zeros(self.shape(True)) basis[np.array([i, i+1, i+2, i+3, i+4])] = (1, 4*(2*i+3)/((i+3)**2), -(2*(i-1)*(i+1)*(i+6)*(2*i+5)/((i+3)**2*(i+4)*(2*i+7))), \ -4*(i+1)**2*(2*i+3)/((i+3)**2*(i+4)**2), \ (i+1)**2*(i+2)**2*(2*i+3)/((i+3)**2*(i+4)**2*(2*i+7))) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) else: X = sympy.symbols('x', real=True) output_array[:] = sympy.lambdify(X, self.sympy_basis(i, X).diff(X, k))(x) return output_array def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = Function(self.get_orthogonal()) else: output_array.fill(0) self.set_factor_arrays(input_array) output_array = self.set_w_hat(output_array, input_array, self._factor1, self._factor2) self.bc.add_to_orthogonal(output_array, input_array) return output_array def slice(self): return slice(0, self.N-4) def eval(self, x, u, output_array=None): if output_array is None: output_array = np.zeros(x.shape, dtype=self.dtype) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] self.set_factor_arrays(u) output_array[:] = leg.legval(x, u[:-4]) w_hat[1:-3] = self._factor1*u[:-4] w_hat[0] = 0 output_array += leg.legval(x, w_hat[:-3]) w_hat[2:-2] = self._factor2*u[:-4] w_hat[:2] = 0 output_array += leg.legval(x, w_hat[:-2]) w_hat[3:-1] = self._factor3*u[:-4] w_hat[:3] = 0 output_array += leg.legval(x, w_hat[:-1]) w_hat[4:] = self._factor3*u[:-4] w_hat[:4] = 0 output_array += leg.legval(x, w_hat) return output_array def get_bc_basis(self): if self._bc_basis: return self._bc_basis self._bc_basis = BCBeamFixedFree(self.N, quad=self.quad, domain=self.domain, coordinates=self.coors.coordinates) return self._bc_basis def get_refined(self, N): return BeamFixedFree(N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_dealiased(self, padding_factor=1.5, dealias_direct=False): return BeamFixedFree(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_unplanned(self): return BeamFixedFree(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) class UpperDirichlet(LegendreBase): """Legendre function space with homogeneous Dirichlet boundary conditions on x=1 Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto domain : 2-tuple of floats, optional The computational domain padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", bc=(None, 0), domain=(-1., 1.), dtype=np.float, padding_factor=1, dealias_direct=False, coordinates=None): assert quad == "LG" LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) from shenfun.tensorproductspace import BoundaryValues self._factor = np.ones(1) self._bc_basis = None self.bc = BoundaryValues(self, bc=bc) @staticmethod def boundary_condition(): return 'UpperDirichlet' @property def has_nonhomogeneous_bcs(self): return self.bc.has_nonhomogeneous_bcs() def is_scaled(self): return False def _composite(self, V, argument=0): P = np.zeros(V.shape) P[:, :-1] = V[:, :-1] - V[:, 1:] if argument == 1: # if trial function P[:, -1] = (V[:, 0] + V[:, 1])/2 # x = +1 return P def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = np.zeros_like(input_array) else: output_array.fill(0) s0 = self.sl[slice(0, -1)] s1 = self.sl[slice(1, None)] output_array[s0] = input_array[s0] output_array[s1] -= input_array[s0] self.bc.add_to_orthogonal(output_array, input_array) return output_array def slice(self): return slice(0, self.N-1) def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i < self.N-1: return sympy.legendre(i, x)-sympy.legendre(i+1, x) assert i == self.N-1 return 0.5*(1+x) def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i < self.N-1: output_array[:] = eval_legendre(i, x) - eval_legendre(i+1, x) elif i == self.N-1: output_array[:] = 0.5*(1+x) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) if output_array is None: output_array = np.zeros(x.shape) x = np.atleast_1d(x) if i < self.N-1: basis = np.zeros(self.shape(True)) basis[np.array([i, i+1])] = (1, -1) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) else: if k == 1: output_array[:] = 0.5 else: output_array[:] = 0 return output_array def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.si[-1]] = 0 def eval(self, x, u, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape, dtype=self.dtype) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] output_array[:] = leg.legval(x, u[:-1]) w_hat[1:] = u[:-1] output_array -= leg.legval(x, w_hat) output_array += 0.5*u[-1]*(1+x) return output_array def get_bc_basis(self): if self._bc_basis: return self._bc_basis self._bc_basis = BCUpperDirichlet(self.N, quad=self.quad, domain=self.domain, coordinates=self.coors.coordinates) return self._bc_basis def get_refined(self, N): return UpperDirichlet(N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_dealiased(self, padding_factor=1.5, dealias_direct=False): return UpperDirichlet(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_unplanned(self): return UpperDirichlet(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) class ShenBiPolar(LegendreBase): """Legendre function space for the Biharmonic equation in polar coordinates Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto domain : 2-tuple of floats, optional The computational domain padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", domain=(-1., 1.), dtype=np.float, padding_factor=1, dealias_direct=False, coordinates=None): assert quad == "LG" LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) @staticmethod def boundary_condition(): return 'BiPolar' @property def has_nonhomogeneous_bcs(self): return False def to_ortho(self, input_array, output_array=None): raise(NotImplementedError) def slice(self): return slice(0, self.N-4) def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): return (1-x)**2*(1+x)**2*(sympy.legendre(i+1, x).diff(x, 1)) def evaluate_basis(self, x=None, i=0, output_array=None): output_array = SpectralBase.evaluate_basis(self, x=x, i=i, output_array=output_array) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): output_array = SpectralBase.evaluate_basis_derivative(self, x=x, i=i, k=k, output_array=output_array) return output_array def evaluate_basis_all(self, x=None, argument=0): if x is None: #x = self.mesh(False, False) x = self.mpmath_points_and_weights()[0] output_array = np.zeros((x.shape[0], self.N)) for j in range(self.N-4): output_array[:, j] = self.evaluate_basis(x, j, output_array=output_array[:, j]) return output_array def evaluate_basis_derivative_all(self, x=None, k=0, argument=0): if x is None: x = self.mpmath_points_and_weights()[0] V = np.zeros((x.shape[0], self.N)) for i in range(self.N-2): V[:, i] = self.evaluate_basis_derivative(x, i, k, output_array=V[:, i]) return V def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.sl[slice(-4, None)]] = 0 def eval(self, x, u, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape, dtype=self.dtype) else: output_array.fill(0) x = self.map_reference_domain(x) fj = self.evaluate_basis_all(x) output_array[:] = np.dot(fj, u) return output_array class ShenBiPolar0(LegendreBase): """Legendre function space for biharmonic basis for polar coordinates Homogeneous Dirichlet and Neumann boundary conditions. Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss 4-tuple of numbers, optional The values of the 4 boundary conditions at x=(-1, 1). The two Dirichlet first and then the Neumann. domain : 2-tuple of floats, optional The computational domain padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", domain=(-1., 1.), padding_factor=1, dealias_direct=False, dtype=np.float, coordinates=None): assert quad == "LG" LegendreBase.__init__(self, N, quad="LG", domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) self._factor1 = np.zeros(0) self._factor2 = np.zeros(0) self._factor3 = np.zeros(0) @staticmethod def boundary_condition(): return 'BiPolar0' @property def has_nonhomogeneous_bcs(self): return False def _composite(self, V, argument=0): P = np.zeros_like(V) k = np.arange(V.shape[1]).astype(np.float)[:-3] P[:, :-3] = V[:, :-3] - ((2*k+3)*(k+4)/(2*k+5)/(k+2))*V[:, 1:-2] - (k*(k+1)/(k+2)/(k+3))*V[:, 2:-1] + (k+1)*(2*k+3)/(k+3)/(2*k+5)*V[:, 3:] return P def set_factor_arrays(self, v): s = self.sl[self.slice()] if not self._factor1.shape == v[s].shape: k = self.wavenumbers().astype(np.float) self._factor1 = (-(2*k+3)*(k+4)/(2*k+5)/(k+2)).astype(float) self._factor2 = (-k*(k+1)/(k+2)/(k+3)).astype(float) self._factor3 = ((k+1)*(2*k+3)/(k+3)/(2*k+5)).astype(float) #@optimizer def set_w_hat(self, w_hat, fk, f1, f2, f3): # pragma: no cover s = self.sl[self.slice()] s1 = self.sl[slice(1, -2)] s2 = self.sl[slice(2, -1)] s3 = self.sl[slice(3, None)] w_hat[s] = fk[s] w_hat[s1] += f1*fk[s] w_hat[s2] += f2*fk[s] w_hat[s3] += f3*fk[s] return w_hat def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): #x = self.map_reference_domain(x) return (sympy.legendre(i, x) -(2*i+3)*(i+4)/(2*i+5)/(i+2)*sympy.legendre(i+1, x) -i*(i+1)/(i+2)/(i+3)*sympy.legendre(i+2, x) +(i+1)*(2*i+3)/(i+3)/(2*i+5)*sympy.legendre(i+3, x)) #return # (sympy.legendre(i, x) -(2*i+3)*(i+4)/(2*i+5)*sympy.legendre(i+1, x) -i*(i+1)/(i+2)/(i+3)*sympy.legendre(i+2, x) +(i+1)*(i+2)*(2*i+3)/(i+3)/(2*i+5)*sympy.legendre(i+3, x)) def evaluate_basis(self, x=None, i=0, output_array=None): output_array = SpectralBase.evaluate_basis(self, x=x, i=i, output_array=output_array) return output_array #def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): # output_array = SpectralBase.evaluate_basis_derivative(self, x=x, i=i, k=k, output_array=output_array) # return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i < self.N-3: basis = np.zeros(self.shape(True)) basis[np.array([i, i+1, i+2, i+3])] = (1, -(2*i+3)*(i+4)/(2*i+5)/(i+2), -i*(i+1)/(i+2)/(i+3), (i+1)*(2*i+3)/(i+3)/(2*i+5)) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) else: raise RuntimeError return output_array def evaluate_basis_derivative_all(self, x=None, k=0, argument=0): if x is None: x = self.mpmath_points_and_weights()[0] V = np.zeros((x.shape[0], self.N)) for i in range(self.N-3): V[:, i] = self.evaluate_basis_derivative(x, i, k, output_array=V[:, i]) return V def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = np.zeros_like(input_array) else: output_array.fill(0) self.set_factor_arrays(input_array) output_array = self.set_w_hat(output_array, input_array, self._factor1, self._factor2, self._factor3) return output_array def slice(self): return slice(0, self.N-3) def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.sl[slice(-3, None)]] = 0 def eval(self, x, u, output_array=None): if output_array is None: output_array = np.zeros(x.shape, dtype=self.dtype) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] self.set_factor_arrays(u) output_array[:] = leg.legval(x, u[:-3]) w_hat[1:-2] = self._factor1*u[:-3] output_array += leg.legval(x, w_hat[:-2]) w_hat[2:-1] = self._factor2*u[:-3] w_hat[:2] = 0 output_array += leg.legval(x, w_hat) w_hat[3:] = self._factor3*u[:-3] w_hat[:3] = 0 output_array += leg.legval(x, w_hat) return output_array class DirichletNeumann(LegendreBase): """Function space for mixed Dirichlet/Neumann boundary conditions u(-1)=0, u'(1)=0 Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto bc : tuple of numbers Boundary conditions at edges of domain domain : 2-tuple of floats, optional The computational domain scaled : bool, optional Whether or not to scale test functions with 1/sqrt(4k+6). Scaled test functions give a stiffness matrix equal to the identity matrix. padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", bc=(0., 0.), domain=(-1., 1.), dtype=np.float, padding_factor=1, dealias_direct=False, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) from shenfun.tensorproductspace import BoundaryValues self._factor1 = np.ones(1) self._factor2 = np.ones(1) self._bc_basis = None self.bc = BoundaryValues(self, bc=bc) @staticmethod def boundary_condition(): return 'DirichletNeumann' @property def has_nonhomogeneous_bcs(self): return self.bc.has_nonhomogeneous_bcs() def set_factor_array(self, v): """Set intermediate factor arrays""" s = self.sl[self.slice()] if not self._factor1.shape == v[s].shape: k = self.wavenumbers().astype(float) self._factor1 = ((2*k+3)/(k+2)**2).astype(float) self._factor2 = -(((k+1)/(k+2))**2).astype(float) def _composite(self, V, argument=0): P = np.zeros_like(V) k = np.arange(V.shape[1]).astype(np.float)[:-2] P[:, :-2] = (V[:, :-2] +((2*k+3)/(k+2)**2)*V[:, 1:-1] -(((k+1)/(k+2))**2)*V[:, 2:]) if argument == 1: P[:, -2] = V[:, 0] P[:, -1] = V[:, 0]+V[:, 1] return P def set_w_hat(self, w_hat, fk, f1, f2): s = self.sl[self.slice()] s1 = self.sl[slice(1, -1)] s2 = self.sl[slice(2, None)] w_hat[s] = fk[s] w_hat[s1] += f1*fk[s] w_hat[s2] += f2*fk[s] return w_hat def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = np.zeros_like(input_array) else: output_array.fill(0) self.set_factor_arrays(input_array) output_array = self.set_w_hat(output_array, input_array, self._factor1, self._factor2) self.bc.add_to_orthogonal(output_array, input_array) return output_array def slice(self): return slice(0, self.N-2) def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.sl[slice(-2, None)]] = 0 def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): assert i < self.N-2 return (sympy.legendre(i, x) +(2*i+3)/(i+2)**2*sympy.legendre(i+1, x) -(i+1)**2/(i+2)**2*sympy.legendre(i+2, x)) def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) output_array[:] = (eval_legendre(i, x) +(2*i+3)/(i+2)**2*eval_legendre(i+1, x) -(i+1)**2/(i+2)**2*eval_legendre(i+2, x)) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) if output_array is None: output_array = np.zeros(x.shape) x = np.atleast_1d(x) basis = np.zeros(self.shape(True)) basis[np.array([i, i+1, i+2])] = (1, (2*i+3)/(i+2)**2, -(i+1)**2/(i+2)**2) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) return output_array def eval(self, x, u, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] self.set_factor_array(w_hat) output_array[:] = leg.legval(x, u[:-2]) w_hat[1:-1] = self._factor1*u[:-2] output_array += leg.legval(x, w_hat) w_hat[2:] = self._factor2*u[:-2] w_hat[:2] = 0 output_array += leg.legval(x, w_hat) output_array += u[-2] + u[-1]*(1+x) return output_array def get_bc_basis(self): if self._bc_basis: return self._bc_basis self._bc_basis = BCDirichletNeumann(self.N, quad=self.quad, domain=self.domain, coordinates=self.coors.coordinates) return self._bc_basis def get_refined(self, N): return self.__class__(N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_dealiased(self, padding_factor=1.5, dealias_direct=False): return self.__class__(self.N, quad=self.quad, dtype=self.dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, domain=self.domain, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_unplanned(self): return self.__class__(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) class NeumannDirichlet(LegendreBase): """Function space for mixed Dirichlet/Neumann boundary conditions u'(-1)=0, u(1)=0 Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto bc : tuple of numbers Boundary conditions at edges of domain domain : 2-tuple of floats, optional The computational domain scaled : bool, optional Whether or not to scale test functions with 1/sqrt(4k+6). Scaled test functions give a stiffness matrix equal to the identity matrix. padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", bc=(0., 0.), domain=(-1., 1.), dtype=np.float, padding_factor=1, dealias_direct=False, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) from shenfun.tensorproductspace import BoundaryValues self._factor1 = np.ones(1) self._factor2 = np.ones(1) self._bc_basis = None self.bc = BoundaryValues(self, bc=bc) @staticmethod def boundary_condition(): return 'NeumannDirichlet' @property def has_nonhomogeneous_bcs(self): return self.bc.has_nonhomogeneous_bcs() def set_factor_array(self, v): """Set intermediate factor arrays""" s = self.sl[self.slice()] if not self._factor1.shape == v[s].shape: k = self.wavenumbers().astype(float) self._factor1 = (-(2*k+3)/(k+2)**2).astype(float) self._factor2 = -((k+1)**2/(k+2)**2).astype(float) def _composite(self, V, argument=0): P = np.zeros_like(V) k = np.arange(V.shape[1]).astype(np.float)[:-2] P[:, :-2] = (V[:, :-2] -((2*k+3)/(k+2)**2)*V[:, 1:-1] -((k+1)**2/(k+2)**2)*V[:, 2:]) if argument == 1: P[:, -2] = V[:, 0]-0.5*V[:, 1]-0.5*V[:, 2] P[:, -1] = V[:, 0] return P def set_w_hat(self, w_hat, fk, f1, f2): # pragma: no cover s = self.sl[self.slice()] s1 = self.sl[slice(1, -1)] s2 = self.sl[slice(2, None)] w_hat[s] = fk[s] w_hat[s1] += f1*fk[s] w_hat[s2] += f2*fk[s] return w_hat def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = np.zeros_like(input_array) else: output_array.fill(0) self.set_factor_arrays(input_array) output_array = self.set_w_hat(output_array, input_array, self._factor1, self._factor2) self.bc.add_to_orthogonal(output_array, input_array) return output_array def slice(self): return slice(0, self.N-2) def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.sl[slice(-2, None)]] = 0 def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): assert i < self.N-2 return (sympy.legendre(i, x) -(2*i+3)/(i+2)**2*sympy.legendre(i+1, x) -(i+1)**2/(i+2)**2*sympy.legendre(i+2, x)) def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) output_array[:] = (eval_legendre(i, x) -(2*i+3)/(i+2)**2*eval_legendre(i+1, x) -(i+1)**2/(i+2)**2*eval_legendre(i+2, x)) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) if output_array is None: output_array = np.zeros(x.shape) x = np.atleast_1d(x) basis = np.zeros(self.shape(True)) basis[np.array([i, i+1, i+2])] = (1, -(2*i+3)/(i+2)**2, -(i+1)**2/(i+2)**2) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) return output_array def eval(self, x, u, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] self.set_factor_array(w_hat) output_array[:] = leg.legval(x, u[:-2]) w_hat[1:-1] = self._factor1*u[:-2] output_array += leg.legval(x, w_hat) w_hat[2:] = self._factor2*u[:-2] w_hat[:2] = 0 output_array += leg.legval(x, w_hat) output_array += u[-1] + u[-2]*(1-0.5*x-0.25*(3*x**2-1)) return output_array def get_bc_basis(self): if self._bc_basis: return self._bc_basis self._bc_basis = BCNeumannDirichlet(self.N, quad=self.quad, domain=self.domain, coordinates=self.coors.coordinates) return self._bc_basis def get_refined(self, N): return self.__class__(N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_dealiased(self, padding_factor=1.5, dealias_direct=False): return self.__class__(self.N, quad=self.quad, dtype=self.dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, domain=self.domain, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_unplanned(self): return self.__class__(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) class UpperDirichletNeumann(LegendreBase): """Function space for mixed Dirichlet/Neumann boundary conditions u(1)=0, u'(1)=0 Parameters ---------- N : int Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto bc : tuple of numbers Boundary conditions at edges of domain domain : 2-tuple of floats, optional The computational domain scaled : bool, optional Whether or not to scale test functions with 1/sqrt(4k+6). Scaled test functions give a stiffness matrix equal to the identity matrix. padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform dtype : data-type, optional Type of input data in real physical space. Will be overloaded when basis is part of a :class:`.TensorProductSpace`. coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) Note ---- This basis is not recommended as it leads to a poorly conditioned stiffness matrix. """ def __init__(self, N, quad="LG", bc=(0., 0.), domain=(-1., 1.), dtype=np.float, padding_factor=1, dealias_direct=False, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, dtype=dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) from shenfun.tensorproductspace import BoundaryValues self._factor1 = np.ones(1) self._factor2 = np.ones(1) self._bc_basis = None self.bc = BoundaryValues(self, bc=bc) @staticmethod def boundary_condition(): return 'UpperDirichletNeumann' @property def has_nonhomogeneous_bcs(self): return self.bc.has_nonhomogeneous_bcs() def set_factor_array(self, v): """Set intermediate factor arrays""" s = self.sl[self.slice()] if not self._factor1.shape == v[s].shape: k = self.wavenumbers().astype(float) self._factor1 = (-(2*k+3)/(k+2)).astype(float) self._factor2 = ((k+1)/(k+2)).astype(float) def _composite(self, V, argument=0): P = np.zeros_like(V) k = np.arange(V.shape[1]).astype(np.float)[:-2] P[:, :-2] = (V[:, :-2] -((2*k+3)/(k+2))*V[:, 1:-1] +((k+1)/(k+2))*V[:, 2:]) if argument == 1: P[:, -2] = V[:, 0] P[:, -1] = V[:, 0]-2*V[:, 1]+V[:, 2] return P def set_w_hat(self, w_hat, fk, f1, f2): s = self.sl[self.slice()] s1 = self.sl[slice(1, -1)] s2 = self.sl[slice(2, None)] w_hat[s] = fk[s] w_hat[s1] += f1*fk[s] w_hat[s2] += f2*fk[s] return w_hat def to_ortho(self, input_array, output_array=None): if output_array is None: output_array = np.zeros_like(input_array) else: output_array.fill(0) self.set_factor_arrays(input_array) output_array = self.set_w_hat(output_array, input_array, self._factor1, self._factor2) self.bc.add_to_orthogonal(output_array, input_array) return output_array def slice(self): return slice(0, self.N-2) def _evaluate_scalar_product(self, fast_transform=False): SpectralBase._evaluate_scalar_product(self) self.scalar_product.output_array[self.sl[slice(-2, None)]] = 0 def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): assert i < self.N-2 return (sympy.legendre(i, x) -(2*i+3)/(i+2)*sympy.legendre(i+1, x) +(i+1)/(i+2)*sympy.legendre(i+2, x)) def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) output_array[:] = (eval_legendre(i, x) -(2*i+3)/(i+2)*eval_legendre(i+1, x) +(i+1)/(i+2)*eval_legendre(i+2, x)) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): if x is None: x = self.mesh(False, False) if output_array is None: output_array = np.zeros(x.shape) x = np.atleast_1d(x) basis = np.zeros(self.shape(True)) basis[np.array([i, i+1, i+2])] = (1, -(2*i+3)/(i+2), (i+1)/(i+2)) basis = leg.Legendre(basis) if k > 0: basis = basis.deriv(k) output_array[:] = basis(x) return output_array def eval(self, x, u, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) x = self.map_reference_domain(x) w_hat = work[(u, 0, True)] self.set_factor_array(w_hat) output_array[:] = leg.legval(x, u[:-2]) w_hat[1:-1] = self._factor1*u[:-2] output_array += leg.legval(x, w_hat) w_hat[2:] = self._factor2*u[:-2] w_hat[:2] = 0 output_array += leg.legval(x, w_hat) output_array += u[-2] + u[-1]*(1-2*x+0.5*(3*x**2-1)) return output_array def get_bc_basis(self): if self._bc_basis: return self._bc_basis self._bc_basis = BCUpperDirichletNeumann(self.N, quad=self.quad, domain=self.domain, coordinates=self.coors.coordinates) return self._bc_basis def get_refined(self, N): return self.__class__(N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_dealiased(self, padding_factor=1.5, dealias_direct=False): return self.__class__(self.N, quad=self.quad, dtype=self.dtype, padding_factor=padding_factor, dealias_direct=dealias_direct, domain=self.domain, coordinates=self.coors.coordinates, bc=self.bc.bc) def get_unplanned(self): return self.__class__(self.N, quad=self.quad, domain=self.domain, dtype=self.dtype, padding_factor=self.padding_factor, dealias_direct=self.dealias_direct, coordinates=self.coors.coordinates, bc=self.bc.bc) class BCDirichlet(LegendreBase): def __init__(self, N, quad="LG", scaled=False, domain=(-1., 1.), coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, coordinates=coordinates) self._scaled = scaled def slice(self): return slice(self.N-2, self.N) def shape(self, forward_output=True): if forward_output: return 2 else: return self.N @staticmethod def boundary_condition(): return 'Apply' def vandermonde(self, x): return leg.legvander(x, 1) @staticmethod def coefficient_matrix(): return np.array([[0.5, -0.5], [0.5, 0.5]]) def _composite(self, V, argument=0): P = np.zeros(V.shape) P[:, 0] = (V[:, 0] - V[:, 1])/2 P[:, 1] = (V[:, 0] + V[:, 1])/2 return P def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i == 0: return 0.5*(1-x) elif i == 1: return 0.5*(1+x) else: raise AttributeError('Only two bases, i < 2') def evaluate_basis(self, x, i=0, output_array=None): assert i < 2 x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0: output_array[:] = 0.5*(1-x) elif i == 1: output_array[:] = 0.5*(1+x) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0 and k == 1: output_array[:] = -0.5 elif i == 1 and k == 1: output_array[:] = 0.5 else: output_array[:] = 0 return output_array class BCNeumann(LegendreBase): def __init__(self, N, quad="LG", scaled=False, domain=(-1., 1.), coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, coordinates=coordinates) self._scaled = scaled def slice(self): return slice(self.N-2, self.N) def shape(self, forward_output=True): if forward_output: return 2 else: return self.N @staticmethod def boundary_condition(): return 'Apply' def vandermonde(self, x): return leg.legvander(x, 2) @staticmethod def coefficient_matrix(): return np.array([[0, 1/2, -1/6], [0, 1/2, 1/6]]) def _composite(self, V, argument=0): P = np.zeros(V[:, :2].shape) P[:, 0] = 0.5*V[:, 1] - 1/6*V[:, 2] P[:, 1] = 0.5*V[:, 1] + 1/6*V[:, 2] return P def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i == 0: return x/2-(3*x**2-1)/3 elif i == 1: return x/2+(3*x**2-1)/3 else: raise AttributeError('Only two bases, i < 2') def evaluate_basis(self, x, i=0, output_array=None): assert i < 2 x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0: output_array[:] = x/2-(3*x**2-1)/3 elif i == 1: output_array[:] = x/2+(3*x**2-1)/3 return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0 and k == 0: output_array[:] = x/2-(3*x**2-1)/3 elif i == 0 and k == 1: output_array[:] = 0.5-2*x elif i == 0 and k == 2: output_array[:] = -2 elif i == 1 and k == 0: output_array[:] = x/2+(3*x**2-1)/3 elif i == 1 and k == 1: output_array[:] = 0.5+2*x elif i == 1 and k == 2: output_array[:] = 2 else: output_array[:] = 0 return output_array class BCBiharmonic(LegendreBase): """Function space for inhomogeneous Biharmonic boundary conditions Parameters ---------- N : int, optional Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto domain : 2-tuple of floats, optional The computational domain scaled : bool, optional Whether or not to use scaled basis padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", domain=(-1., 1.), padding_factor=1, dealias_direct=False, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) def slice(self): return slice(self.N-4, self.N) def shape(self, forward_output=True): if forward_output: return 4 else: return self.N @staticmethod def boundary_condition(): return 'Apply' def vandermonde(self, x): return leg.legvander(x, 3) @staticmethod def coefficient_matrix(): return np.array([[0.5, -0.6, 0, 0.1], [0.5, 0.6, 0, -0.1], [1./6., -1./10., -1./6., 1./10.], [-1./6., -1./10., 1./6., 1./10.]]) def _composite(self, V, argument=0): P = np.tensordot(V[:, :4], self.coefficient_matrix(), (1, 1)) return P def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i < 4: f = 0 for j, c in enumerate(self.coefficient_matrix()[i]): f += c*sympy.legendre(j, x) return f else: raise AttributeError('Only four bases, i < 4') def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) V = self.vandermonde(x) output_array[:] = np.dot(V, self.coefficient_matrix()[i]) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): output_array = SpectralBase.evaluate_basis_derivative(self, x=x, i=i, k=k, output_array=output_array) return output_array class BCBeamFixedFree(LegendreBase): """Function space for inhomogeneous Biharmonic boundary conditions u(-1), u'(-1), u''(1), u'''(1) Parameters ---------- N : int, optional Number of quadrature points quad : str, optional Type of quadrature - LG - Legendre-Gauss - GL - Legendre-Gauss-Lobatto domain : 2-tuple of floats, optional The computational domain scaled : bool, optional Whether or not to use scaled basis padding_factor : float, optional Factor for padding backward transforms. dealias_direct : bool, optional Set upper 1/3 of coefficients to zero before backward transform coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="LG", domain=(-1., 1.), padding_factor=1, dealias_direct=False, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, padding_factor=padding_factor, dealias_direct=dealias_direct, coordinates=coordinates) def slice(self): return slice(self.N-4, self.N) def shape(self, forward_output=True): if forward_output: return 4 else: return self.N @staticmethod def boundary_condition(): return 'Apply' def vandermonde(self, x): return leg.legvander(x, 3) @staticmethod def coefficient_matrix(): return np.array([[1, 0, 0, 0], [1, 1, 0, 0], [2/3, 1, 1/3, 0], [-1, -1.4, -1/3, 1/15]]) def _composite(self, V, argument=0): P = np.tensordot(V[:, :4], self.coefficient_matrix(), (1, 1)) return P def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i < 4: f = 0 for j, c in enumerate(self.coefficient_matrix()[i]): f += c*sympy.legendre(j, x) return f else: raise AttributeError('Only four bases, i < 4') def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) V = self.vandermonde(x) output_array[:] = np.dot(V, self.coefficient_matrix()[i]) return output_array class BCUpperDirichlet(LegendreBase): """Function space for Dirichlet boundary conditions at x=1 Parameters ---------- N : int, optional Number of quadrature points quad : str, optional Type of quadrature - GL - Chebyshev-Gauss-Lobatto - GC - Chebyshev-Gauss domain : 2-tuple of floats, optional The computational domain scaled : bool, optional Whether or not to use scaled basis coordinates: 2- or 3-tuple (coordinate, position vector (, sympy assumptions)), optional Map for curvilinear coordinatesystem. The new coordinate variable in the new coordinate system is the first item. Second item is a tuple for the Cartesian position vector as function of the new variable in the first tuple. Example:: theta = sp.Symbols('x', real=True, positive=True) rv = (sp.cos(theta), sp.sin(theta)) """ def __init__(self, N, quad="GC", domain=(-1., 1.), scaled=False, coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, coordinates=coordinates) def slice(self): return slice(self.N-1, self.N) def shape(self, forward_output=True): if forward_output: return 1 else: return self.N @staticmethod def boundary_condition(): return 'Apply' def vandermonde(self, x): return leg.legvander(x, 1) def coefficient_matrix(self): return np.array([[0.5, 0.5]]) def _composite(self, V, argument=0): P = np.zeros(V[:, :1].shape) P[:, 0] = (V[:, 0] + V[:, 1])/2 return P def sympy_basis(self, i=0, x=sympy.Symbol('x', real=True)): if i == 0: return 0.5*(1+x) else: raise AttributeError('Only one basis, i == 0') def evaluate_basis(self, x, i=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0: output_array[:] = 0.5*(1+x) else: raise AttributeError('Only one basis, i == 0') return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): assert i == 0 x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) output_array[:] = 0 if k == 1: output_array[:] = 0.5 elif k == 0: output_array[:] = 0.5*(1+x) return output_array def evaluate_basis_derivative_all(self, x=None, k=0, argument=0): if x is None: x = self.mesh(False, False) output_array = np.zeros((self.N, 1)) self.evaluate_basis_derivative(x=x, k=k, output_array=output_array[:, 0]) return output_array class BCNeumannDirichlet(LegendreBase): def __init__(self, N, quad="LG", scaled=False, domain=(-1., 1.), coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, coordinates=coordinates) self._scaled = scaled def slice(self): return slice(self.N-2, self.N) def shape(self, forward_output=True): if forward_output: return 2 else: return self.N @staticmethod def boundary_condition(): return 'Apply' def vandermonde(self, x): return leg.legvander(x, 2) @staticmethod def coefficient_matrix(): return np.array([[1, -0.5, -0.5], [1, 0, 0]]) def _composite(self, V, argument=0): P = np.zeros(V[:, :2].shape) P[:, 0] = V[:, 0] - 0.5*V[:, 1] -0.5*V[:, 2] P[:, 1] = V[:, 0] return P def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i == 0: return 1-0.5*x-0.25*(3*x**2-1) elif i == 1: return 1 else: raise AttributeError('Only two bases, i < 2') def evaluate_basis(self, x, i=0, output_array=None): assert i < 2 x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0: output_array[:] = 1-0.5*x-0.25*(3*x**2-1) elif i == 1: output_array[:] = 1 return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0 and k == 0: output_array[:] = 1-0.5*x-0.25*(3*x**2-1) elif i == 0 and k == 1: output_array[:] = -0.5-1.5*x elif i == 0 and k == 2: output_array[:] = -1.5 elif i == 1 and k == 0: output_array[:] = 1 else: output_array[:] = 0 return output_array #def evaluate_basis_derivative_all(self, x=None, k=0, argument=0): # if x is None: # x = self.mesh(False, False) # output_array = np.zeros((self.N, 2)) # self.evaluate_basis_derivative(x=x, i=0, k=k, output_array=output_array[:, 0]) # self.evaluate_basis_derivative(x=x, i=1, k=k, output_array=output_array[:, 1]) # return output_array class BCDirichletNeumann(LegendreBase): def __init__(self, N, quad="LG", domain=(-1., 1.), coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, coordinates=coordinates) def slice(self): return slice(self.N-2, self.N) def shape(self, forward_output=True): if forward_output: return 2 else: return self.N @staticmethod def boundary_condition(): return 'Apply' def vandermonde(self, x): return leg.legvander(x, 1) @staticmethod def coefficient_matrix(): return np.array([[1, 0], [1, 1]]) def _composite(self, V, argument=0): P = np.zeros(V[:, :2].shape) P[:, 0] = V[:, 0] P[:, 1] = V[:, 0] + V[:, 1] return P def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i == 0: return 1 elif i == 1: return 1+x else: raise AttributeError('Only two bases, i < 2') def evaluate_basis(self, x, i=0, output_array=None): assert i < 2 x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0: output_array[:] = 1 elif i == 1: output_array[:] = 1+x return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0 and k == 0: output_array[:] = 1 elif i == 1 and k == 0: output_array[:] = 1+x elif i == 1 and k == 1: output_array[:] = 1 else: output_array[:] = 0 return output_array def evaluate_basis_derivative_all(self, x=None, k=0, argument=0): if x is None: x = self.mesh(False, False) output_array = np.zeros((self.N, 2)) self.evaluate_basis_derivative(x=x, i=0, k=k, output_array=output_array[:, 0]) self.evaluate_basis_derivative(x=x, i=1, k=k, output_array=output_array[:, 1]) return output_array class BCUpperDirichletNeumann(LegendreBase): def __init__(self, N, quad="LG", domain=(-1., 1.), coordinates=None): LegendreBase.__init__(self, N, quad=quad, domain=domain, coordinates=coordinates) def slice(self): return slice(self.N-2, self.N) def shape(self, forward_output=True): if forward_output: return 2 else: return self.N @staticmethod def boundary_condition(): return 'Apply' def vandermonde(self, x): return leg.legvander(x, 2) @staticmethod def coefficient_matrix(): return np.array([[1, 0, 0], [1, -2, 1]]) def _composite(self, V, argument=0): P = np.zeros(V[:, :2].shape) P[:, 0] = V[:, 0] P[:, 1] = V[:, 0] - 2*V[:, 1] + V[:, 2] return P def sympy_basis(self, i=0, x=sympy.symbols('x', real=True)): if i == 0: return 1 elif i == 1: return 1-2*x+0.5*(3*x**2-1) else: raise AttributeError('Only two bases, i < 2') def evaluate_basis(self, x, i=0, output_array=None): assert i < 2 x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0: output_array[:] = 1 elif i == 1: output_array[:] = 1-2*x+0.5*(3*x**2-1) return output_array def evaluate_basis_derivative(self, x=None, i=0, k=0, output_array=None): x = np.atleast_1d(x) if output_array is None: output_array = np.zeros(x.shape) if i == 0 and k == 0: output_array[:] = 1 elif i == 1 and k == 0: output_array[:] = 1-2*x+0.5*(3*x**2-1) elif i == 1 and k == 1: output_array[:] = -2+3*x elif i == 1 and k == 2: output_array[:] = 3 else: output_array[:] = 0 return output_array def evaluate_basis_derivative_all(self, x=None, k=0, argument=0): if x is None: x = self.mesh(False, False) output_array = np.zeros((self.N, 2)) self.evaluate_basis_derivative(x=x, i=0, k=k, output_array=output_array[:, 0]) self.evaluate_basis_derivative(x=x, i=1, k=k, output_array=output_array[:, 1]) return output_array

37.994652

180

0.549864

13,031

99,470

4.060011

0.026322

0.086701

0.011057

0.019053

0.926568

0.914811

0.90175

0.894379

0.882301

0.872737

0

0.02783

0.327727

99,470

2,617

181

38.009171

0.763335

0.202574

0

0.808618

0

0.008578

0.000813

0

0.007834

1

0.144936

false

0

0.011192

0.053721

0.303861

0

null

0

1

0

1

0

null

0

7

653be0c144b40281cb97b06271573c4274e6ed24

106

py

Python

montepython/likelihoods/Planck_lowlTT/__init__.py

emiliobellini/montepython_public

a3b1ba7ef614db21ac737de226648bc3477aca35

[ "MIT" ]

1

2018-04-29T06:48:35.000Z

montepython/likelihoods/Planck_lowlTT/__init__.py

emiliobellini/montepython_public

a3b1ba7ef614db21ac737de226648bc3477aca35

[ "MIT" ]

null

montepython/likelihoods/Planck_lowlTT/__init__.py

emiliobellini/montepython_public

a3b1ba7ef614db21ac737de226648bc3477aca35

[ "MIT" ]

2

2019-10-11T09:46:35.000Z

2019-12-05T14:55:04.000Z

from montepython.likelihood_class import Likelihood_clik class Planck_lowlTT(Likelihood_clik): pass

17.666667

56

0.839623

13

106

6.538462

0.692308

0.329412

0

0.122642

106

5

57

21.2

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1

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true

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1

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null

0

1

0

1

0

7

6547858856bef80d893ade67b98883fc61663bc4

4,243

py

Python

First_Iteration/Cards.py

mehularora8/UNO

32713dab69a5fdc7d49607d3195ef2ad5e5a9795

[ "MIT" ]

null

First_Iteration/Cards.py

mehularora8/UNO

32713dab69a5fdc7d49607d3195ef2ad5e5a9795

[ "MIT" ]

null

First_Iteration/Cards.py

mehularora8/UNO

32713dab69a5fdc7d49607d3195ef2ad5e5a9795

[ "MIT" ]

null

class Card: # Game card. def __init__(self, number, color, ability, wild): # Number on the face of the card self.number = number # Which color is the thing self.color = color # Draw 2 / Reverse etc self.ability = ability # Wild card? self.wild = wild def __eq__(self, other): return (self.number == other.number) and (self.color == other.color) and (self.ability == other.ability) and (self.wild == other.wild) cards = [ Card(0, (255, 0, 0), None, None), Card(1, (255, 0, 0), None, None), Card(2, (255, 0, 0), None, None), Card(3, (255, 0, 0), None, None), Card(4, (255, 0, 0), None, None), Card(5, (255, 0, 0), None, None), Card(6, (255, 0, 0), None, None), Card(7, (255, 0, 0), None, None), Card(8, (255, 0, 0), None, None), Card(9, (255, 0, 0), None, None), Card(1, (255, 0, 0), None, None), Card(2, (255, 0, 0), None, None), Card(3, (255, 0, 0), None, None), Card(4, (255, 0, 0), None, None), Card(5, (255, 0, 0), None, None), Card(6, (255, 0, 0), None, None), Card(7, (255, 0, 0), None, None), Card(8, (255, 0, 0), None, None), Card(9, (255, 0, 0), None, None), # Ability cards Card("d2", (255, 0, 0), "d2", None), Card("d2", (255, 0, 0), "d2", None), Card("skip", (255, 0, 0), "skip", None), Card("skip", (255, 0, 0), "skip", None), Card("rev", (255, 0, 0), "rev", None), Card("rev", (255, 0, 0), "rev", None), #Green Card(0, (0, 255, 0), None, None), Card(1, (0, 255, 0), None, None), Card(2, (0, 255, 0), None, None), Card(3, (0, 255, 0), None, None), Card(4, (0, 255, 0), None, None), Card(5, (0, 255, 0), None, None), Card(6, (0, 255, 0), None, None), Card(7, (0, 255, 0), None, None), Card(8, (0, 255, 0), None, None), Card(9, (0, 255, 0), None, None), Card(1, (0, 255, 0), None, None), Card(2, (0, 255, 0), None, None), Card(3, (0, 255, 0), None, None), Card(4, (0, 255, 0), None, None), Card(5, (0, 255, 0), None, None), Card(6, (0, 255, 0), None, None), Card(7, (0, 255, 0), None, None), Card(8, (0, 255, 0), None, None), Card(9, (0, 255, 0), None, None), # Ability cards Card("d2", (0, 255, 0), "d2", None), Card("d2", (0, 255, 0), "d2", None), Card("skip", (0, 255, 0), "skip", None), Card("skip", (0, 255, 0), "skip", None), Card("rev", (0, 255, 0), "rev", None), Card("rev", (0, 255, 0), "rev", None), # Blue Card(0, (0, 0, 255), None, None), Card(1, (0, 0, 255), None, None), Card(2, (0, 0, 255), None, None), Card(3, (0, 0, 255), None, None), Card(4, (0, 0, 255), None, None), Card(5, (0, 0, 255), None, None), Card(6, (0, 0, 255), None, None), Card(7, (0, 0, 255), None, None), Card(8, (0, 0, 255), None, None), Card(9, (0, 0, 255), None, None), Card(1, (0, 0, 255), None, None), Card(2, (0, 0, 255), None, None), Card(3, (0, 0, 255), None, None), Card(4, (0, 0, 255), None, None), Card(5, (0, 0, 255), None, None), Card(6, (0, 0, 255), None, None), Card(7, (0, 0, 255), None, None), Card(8, (0, 0, 255), None, None), Card(9, (0, 0, 255), None, None), # Ability cards Card("d2", (0, 0, 255), "d2", None), Card("d2", (0, 0, 255), "d2", None), Card("skip", (0, 0, 255), "skip", None), Card("skip", (0, 0, 255), "skip", None), Card("rev", (0, 0, 255), "rev", None), Card("rev", (0, 0, 255), "rev", None), # Yellow Card(0, (250, 192, 32), None, None), Card(1, (250, 192, 32), None, None), Card(2, (250, 192, 32), None, None), Card(3, (250, 192, 32), None, None), Card(4, (250, 192, 32), None, None), Card(5, (250, 192, 32), None, None), Card(6, (250, 192, 32), None, None), Card(7, (250, 192, 32), None, None), Card(8, (250, 192, 32), None, None), Card(9, (250, 192, 32), None, None), Card(1, (250, 192, 32), None, None), Card(2, (250, 192, 32), None, None), Card(3, (250, 192, 32), None, None), Card(4, (250, 192, 32), None, None), Card(5, (250, 192, 32), None, None), Card(6, (250, 192, 32), None, None), Card(7, (250, 192, 32), None, None), Card(8, (250, 192, 32), None, None), Card(9, (250, 192, 32), None, None), # Ability cards Card("d2", (250, 192, 32), "d2", None), Card("d2", (250, 192, 32), "d2", None), Card("skip", (250, 192, 32), "skip", None), Card("skip", (250, 192, 32), "skip", None), Card("rev", (250, 192, 32), "rev", None), Card("rev", (250, 192, 32), "rev", None), ]

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Python

AMR-Policies-Other/Environment.py

irom-lab/AMR-Policies

43552ca0ddcd584a9faa12b5588874bac41bd205

[ "MIT" ]

2

2020-10-29T02:21:27.000Z

2021-07-26T07:38:23.000Z

AMR-Policies-Other/Environment.py

irom-lab/AMR-Policies

43552ca0ddcd584a9faa12b5588874bac41bd205

[ "MIT" ]

null

AMR-Policies-Other/Environment.py

irom-lab/AMR-Policies

43552ca0ddcd584a9faa12b5588874bac41bd205

[ "MIT" ]

null

import pybullet import pybullet_utils.bullet_client as bc import pybullet_data import numpy as np from abc import ABC, abstractmethod class SetEnvironment(): def setup_pybullet(self, robot_file, parallel=False): robot_radius = self.robot.robot_radius if parallel: if self.gui: print("Warning: Can only have one thread be a gui") p = bc.BulletClient(connection_mode=pybullet.GUI) visual_shape_id = p.createVisualShape(pybullet.GEOM_SPHERE, radius=robot_radius, rgbaColor=[0, 0, 0, 0]) else: p = bc.BulletClient(connection_mode=pybullet.DIRECT) visual_shape_id = -1 p.setAdditionalSearchPath(pybullet_data.getDataPath()) else: if self.gui: pybullet.connect(pybullet.GUI) p = pybullet # This just makes sure that the sphere is not visible (we only use the sphere for collision checking) visual_shape_id = p.createVisualShape(pybullet.GEOM_SPHERE, radius=robot_radius, rgbaColor=[0, 0, 0, 0]) else: pybullet.connect(pybullet.DIRECT) p = pybullet visual_shape_id = -1 p.loadURDF("./URDFs/plane.urdf") # Ground plane husky = p.loadURDF(robot_file, globalScaling=0.5) # Load robot from URDF col_sphere_id = pybullet.createCollisionShape(pybullet.GEOM_SPHERE, radius=robot_radius) # Sphere mass = 0 sphere = pybullet.createMultiBody(mass, col_sphere_id, visual_shape_id) self.p = p self.husky = husky self.sphere = sphere def set_gui(self, gui): self.p.disconnect() self.gui = gui self.setup_pybullet() class Environment(ABC): @abstractmethod def generate_obstacles(self): pass # Discrete Maze Environment #********************************************************************************************************************** class GridWorld(Environment): ''' ENVIRONMENT DESCRIPTION: Grid World size 20 x 20 ''' def __init__(self, size, robot, empty=False, filename='None'): self.size = size self.robot = robot self.empty = empty self.data_filename = filename def generate_obstacles(self): maze = np.zeros((20,20)) return maze # Random Obstacle Environment #********************************************************************************************************************** class RandomObstacle(Environment, SetEnvironment): ''' ENVIRONMENT DESCRIPTION: Maze Navigation environment. Walled maze with two obstacles placed in locations from files. Locations were uniformly sampled: y1 drawn from set [y_min + 5.2, y_min + 7.2], y2 drawn from set [y_min + 2, y_min + 8] ''' def __init__(self, robot, parallel=False, gui=False, x_min=-5.0, x_max=5.0, y_min=0.0, y_max=10.0, task=None, mode='train', filename=None): self.parallel = parallel self.gui = gui self.robot = robot self.height_obs = 100*robot.height self.x_lim = [x_min, x_max] self.y_lim = [y_min, y_max] self.p = None self.husky = None self.sphere = None self.setup_pybullet(self.robot.get_robot()) self.task = task self.mode = mode self.data_filename = filename if self.mode is 'train': self.sample_y1 = np.load("./envs/train_Maze_250_y1.npy") self.sample_y2 = np.load("./envs/train_Maze_250_y2.npy") else: self.sample_y1 = np.load("./envs/test_Maze_20_y1.npy") self.sample_y2 = np.load("./envs/test_Maze_20_y2.npy") def generate_obstacles(self, s): if self.parallel: self.setup_pybullet(self.robot.get_robot(), self.parallel) p = self.p x_lim = self.x_lim y_lim = self.y_lim numObs = 0 heightObs = self.height_obs numEnvParts = 9 linkMasses = [None] * (numObs + numEnvParts) colIdxs = [None] * (numObs + numEnvParts) visIdxs = [None] * (numObs + numEnvParts) posObs = [None] * (numObs + numEnvParts) orientObs = [None] * (numObs + numEnvParts) parentIdxs = [None] * (numObs + numEnvParts) linkInertialFramePositions = [None] * (numObs + numEnvParts) linkInertialFrameOrientations = [None] * (numObs + numEnvParts) linkJointTypes = [None] * (numObs + numEnvParts) linkJointAxis = [None] * (numObs + numEnvParts) for obs in range(numObs + numEnvParts): linkMasses[obs] = 0.0 visIdxs[obs] = -1 parentIdxs[obs] = 0 linkInertialFramePositions[obs] = [0, 0, 0] linkInertialFrameOrientations[obs] = [0, 0, 0, 1] linkJointTypes[obs] = p.JOINT_FIXED linkJointAxis[obs] = np.array([0, 0, 1]) orientObs[obs] = [0, 0, 0, 1] # Left wall posObs[numObs] = [x_lim[0], (y_lim[0] + y_lim[1] - 1) / 2.0, 0.0] colIdxs[numObs] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0] + 1) / 2, heightObs / 2]) visIdxs[numObs] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0] + 1) / 2, heightObs / 2], rgbaColor=[0.5, 0.5, 0.5, 1]) # Right wall posObs[numObs + 1] = [x_lim[1], (y_lim[0] + y_lim[1] - 1) / 2.0, 0.0] colIdxs[numObs + 1] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0] + 1) / 2, heightObs / 2]) visIdxs[numObs + 1] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0] + 1) / 2, heightObs / 2], rgbaColor=[0.5, 0.5, 0.5, 1]) # Top Wall orientObs[numObs + 2] = [0, 0, np.sqrt(2) / 2, np.sqrt(2) / 2] posObs[numObs + 2] = [(x_lim[0] + x_lim[1]) / 2.0, y_lim[1], 0.0] colIdxs[numObs + 2] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2]) visIdxs[numObs + 2] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2], rgbaColor=[0.5, 0.5, 0.5, 1]) # Bottom Wall orientObs[numObs + 6] = [0, 0, np.sqrt(2) / 2, np.sqrt(2) / 2] posObs[numObs + 6] = [(x_lim[0] + x_lim[1]) / 2.0, y_lim[0] - 1, 0.0] colIdxs[numObs + 6] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2]) visIdxs[numObs + 6] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2], rgbaColor=[0.5, 0.5, 0.5, 1]) if self.mode is 'test3': # Left wall posObs[numObs] = [x_lim[0], (y_lim[0] + y_lim[1] - 1) / 2.0, 0.0] colIdxs[numObs] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0] + 1) / 2, heightObs / 2]) visIdxs[numObs] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0] + 1) / 2, heightObs / 2], rgbaColor=[0.27, 0.89, 0.96, 1]) # Right wall posObs[numObs + 1] = [x_lim[1], (y_lim[0] + y_lim[1] - 1) / 2.0, 0.0] colIdxs[numObs + 1] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0] + 1) / 2, heightObs / 2]) visIdxs[numObs + 1] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0] + 1) / 2, heightObs / 2], rgbaColor=[0.49, 0.59, 0.49, 1]) # Top Wall orientObs[numObs + 2] = [0, 0, np.sqrt(2) / 2, np.sqrt(2) / 2] posObs[numObs + 2] = [(x_lim[0] + x_lim[1]) / 2.0, y_lim[1], 0.0] colIdxs[numObs + 2] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2]) visIdxs[numObs + 2] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2], rgbaColor=[0.74, 0.69, 0.36, 1]) # Bottom Wall orientObs[numObs + 6] = [0, 0, np.sqrt(2) / 2, np.sqrt(2) / 2] posObs[numObs + 6] = [(x_lim[0] + x_lim[1]) / 2.0, y_lim[0] - 1, 0.0] colIdxs[numObs + 6] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2]) visIdxs[numObs + 6] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2], rgbaColor=[0.5, 0.5, 0.5, 1]) #Two obstacles # Obstacle 1 posObs[numObs + 3] = [x_lim[0] + 3, self.sample_y1[s], 0] colIdxs[numObs + 3] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.65, 1.5, heightObs / 2]) visIdxs[numObs + 3] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.65, 1.5, heightObs / 2], rgbaColor=[0.69, 0.35, 0.47, 1]) # Obstacle 2 posObs[numObs + 4] = [x_lim[1] - 2., self.sample_y2[s], 0] colIdxs[numObs + 4] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[2, 0.65, heightObs / 2]) visIdxs[numObs + 4] = p.createVisualShape(p.GEOM_BOX, halfExtents=[2, 0.65, heightObs / 2], rgbaColor=[0.38, 0.03, 0.63, 1]) elif self.mode is 'test2': # Two obstacles # Obstacle 1 posObs[numObs + 3] = [x_lim[0] + 3, self.sample_y1[s], 0] colIdxs[numObs + 3] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.65, 1.5, heightObs / 2]) visIdxs[numObs + 3] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.65, 1.5, heightObs / 2], rgbaColor=[0, 0, 1, 1]) # Obstacle 2 posObs[numObs + 4] = [x_lim[1] - 2., self.sample_y2[s], 0] colIdxs[numObs + 4] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[2, 0.65, heightObs / 2]) visIdxs[numObs + 4] = p.createVisualShape(p.GEOM_BOX, halfExtents=[2, 0.65, heightObs / 2], rgbaColor=[1, 0, 0, 1]) else: # Two obstacles # Obstacle 1 posObs[numObs + 3] = [x_lim[0] + 3, self.sample_y1[s], 0] colIdxs[numObs + 3] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.65, 1.5, heightObs / 2]) visIdxs[numObs + 3] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.65, 1.5, heightObs / 2], rgbaColor=[1, 0, 0, 1]) # Obstacle 2 posObs[numObs + 4] = [x_lim[1] - 2., self.sample_y2[s], 0] colIdxs[numObs + 4] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[2, 0.65, heightObs / 2]) visIdxs[numObs + 4] = p.createVisualShape(p.GEOM_BOX, halfExtents=[2, 0.65, heightObs / 2], rgbaColor=[0, 0, 1, 1]) # Goal Marker if self.task is not None: posObs[numObs + 5] = [self.task.goal[0], self.task.goal[1], 0] visIdxs[numObs + 5] = p.createVisualShape(p.GEOM_CYLINDER, radius=0.5, length=2.5, rgbaColor=[0., 1., 0., 1]) obsUid = p.createMultiBody(baseCollisionShapeIndex=-1, baseVisualShapeIndex=-1, basePosition=[0, 0, 0], baseOrientation=[0, 0, 0, 1], baseInertialFramePosition=[0, 0, 0], baseInertialFrameOrientation=[0, 0, 0, 1], linkMasses=linkMasses, linkCollisionShapeIndices=colIdxs, linkVisualShapeIndices=visIdxs, linkPositions=posObs, linkOrientations=orientObs, linkParentIndices=parentIdxs, linkInertialFramePositions=linkInertialFramePositions, linkInertialFrameOrientations=linkInertialFrameOrientations, linkJointTypes=linkJointTypes, linkJointAxis=linkJointAxis) p.resetDebugVisualizerCamera(cameraDistance=15., cameraYaw=0., cameraPitch=-85., cameraTargetPosition=[0, 5, 0]) return obsUid # Corridor Environment #********************************************************************************************************************** class Corridor(Environment, SetEnvironment): ''' ENVIRONMENT DESCRIPTION: One red corridor, one green corridor with randomly chosen colored walls ''' def __init__(self, robot, parallel=False, gui=False, x_min=-5.0, x_max=5.0, y_min=0.0, y_max=10.0): self.parallel = parallel self.gui = gui self.robot = robot self.height_obs = 100 * robot.height self.x_lim = [x_min, x_max] self.y_lim = [y_min, y_max] self.p = None self.husky = None self.sphere = None self.setup_pybullet(self.robot.get_robot()) def generate_obstacles(self): p = self.p x_lim = self.x_lim y_lim = self.y_lim numObs = 0 heightObs = self.height_obs rgb_range = np.linspace(0, 1, 11) numEnvParts = 8 linkMasses = [None] * (numObs + numEnvParts) colIdxs = [None] * (numObs + numEnvParts) visIdxs = [None] * (numObs + numEnvParts) posObs = [None] * (numObs + numEnvParts) orientObs = [None] * (numObs + numEnvParts) parentIdxs = [None] * (numObs + numEnvParts) linkInertialFramePositions = [None] * (numObs + numEnvParts) linkInertialFrameOrientations = [None] * (numObs + numEnvParts) linkJointTypes = [None] * (numObs + numEnvParts) linkJointAxis = [None] * (numObs + numEnvParts) for obs in range(numObs + numEnvParts): linkMasses[obs] = 0.0 visIdxs[obs] = -1 parentIdxs[obs] = 0 linkInertialFramePositions[obs] = [0, 0, 0] linkInertialFrameOrientations[obs] = [0, 0, 0, 1] linkJointTypes[obs] = p.JOINT_FIXED linkJointAxis[obs] = np.array([0, 0, 1]) orientObs[obs] = [0, 0, 0, 1] # Left wall posObs[numObs] = [x_lim[0], (y_lim[0] + y_lim[1]) / 2.0, 0.0] colIdxs[numObs] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0]) / 2.0, heightObs / 2]) visIdxs[numObs] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0]) / 2.0, heightObs / 2], rgbaColor=[np.random.choice(rgb_range, 1), np.random.choice(rgb_range, 1), np.random.choice(rgb_range, 1), 1]) # Right wall posObs[numObs + 1] = [x_lim[1], (y_lim[0] + y_lim[1]) / 2.0, 0.0] colIdxs[numObs + 1] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0]) / 2.0, heightObs / 2]) visIdxs[numObs + 1] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (y_lim[1] - y_lim[0]) / 2.0, heightObs / 2], rgbaColor=[np.random.choice(rgb_range, 1), np.random.choice(rgb_range, 1), np.random.choice(rgb_range, 1), 1]) # Bottom wall orientObs[numObs + 2] = [0, 0, np.sqrt(2) / 2, np.sqrt(2) / 2] posObs[numObs + 2] = [(x_lim[0] + x_lim[1]) / 2.0, y_lim[0], 0.0] colIdxs[numObs + 2] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2]) visIdxs[numObs + 2] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2], rgbaColor=[np.random.choice(rgb_range, 1), np.random.choice(rgb_range, 1), np.random.choice(rgb_range, 1), 1]) # Top wall orientObs[numObs + 3] = [0, 0, np.sqrt(2) / 2, np.sqrt(2) / 2] posObs[numObs + 3] = [(x_lim[0] + x_lim[1]) / 2.0, y_lim[1], 0.0] colIdxs[numObs + 3] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2]) visIdxs[numObs + 3] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, (x_lim[1] - x_lim[0]) / 2.0, heightObs / 2], rgbaColor=[np.random.choice(rgb_range, 1), np.random.choice(rgb_range, 1), np.random.choice(rgb_range, 1), 1]) # Corridor 1 posObs[numObs + 4] = [-1.1, 1.5, 0.0] colIdxs[numObs + 4] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, 1.5, heightObs / 2]) visIdxs[numObs + 4] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, 1.5, heightObs / 2], rgbaColor=[0, 1, 0, 1]) posObs[numObs + 5] = [-0.1, 1.5, 0.0] colIdxs[numObs + 5] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, 1.5, heightObs / 2]) visIdxs[numObs + 5] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, 1.5, heightObs / 2], rgbaColor=[0, 1, 0, 1]) # Corridor 2 posObs[numObs + 6] = [0.1, 1.5, 0.0] colIdxs[numObs + 6] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, 1.5, heightObs / 2]) visIdxs[numObs + 6] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, 1.5, heightObs / 2], rgbaColor=[1, 0, 0, 1]) posObs[numObs + 7] = [1.1, 1.5, 0.0] colIdxs[numObs + 7] = p.createCollisionShape(p.GEOM_BOX, halfExtents=[0.1, 1.5, heightObs / 2]) visIdxs[numObs + 7] = p.createVisualShape(p.GEOM_BOX, halfExtents=[0.1, 1.5, heightObs / 2], rgbaColor=[1, 0, 0, 1]) obsUid = p.createMultiBody(baseCollisionShapeIndex=-1, baseVisualShapeIndex=-1, basePosition=[0, 0, 0], baseOrientation=[0, 0, 0, 1], baseInertialFramePosition=[0, 0, 0], baseInertialFrameOrientation=[0, 0, 0, 1], linkMasses=linkMasses, linkCollisionShapeIndices=colIdxs, linkVisualShapeIndices=visIdxs, linkPositions=posObs, linkOrientations=orientObs, linkParentIndices=parentIdxs, linkInertialFramePositions=linkInertialFramePositions, linkInertialFrameOrientations=linkInertialFrameOrientations, linkJointTypes=linkJointTypes, linkJointAxis=linkJointAxis) p.resetDebugVisualizerCamera(cameraDistance=15., cameraYaw=0., cameraPitch=-85., cameraTargetPosition=[0, 5, 0]) return obsUid

50.344828

121

0.470183

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21,900

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null

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1

0

1

0

null

0

7

3317f3d8306af2b3d6515d91ad539863ec86664f

2,861

py

Python

tests/resolver_tests.py

Ginkooo/ginkooowebsite

cd303c8aed7d17ce28e4593f0459ce37815dd36d

[ "MIT" ]

null

tests/resolver_tests.py

Ginkooo/ginkooowebsite

cd303c8aed7d17ce28e4593f0459ce37815dd36d

[ "MIT" ]

null

tests/resolver_tests.py

Ginkooo/ginkooowebsite

cd303c8aed7d17ce28e4593f0459ce37815dd36d

[ "MIT" ]

null

from unittest import TestCase import src.resolver as resolver from config import settings class ResolverTests(TestCase): def check_can_get_parts_of_url(self): urls = [ '/', '/foo', '/foo/', '/foo/bar', '/foo/bar/', '/foo/bar/car/lar/', '/foo/bar/car/lar/dar/', '/foo/bar/car/?foo=bar&mar=far', '/foo/bar?foo=bar&mar=far/', ] fn = resolver.get_parts_of_url results = [] for url in urls: results.append(fn(url)) controller, action, params, qs_params = results[0] self.assertEqual(settings.DEFAULT_CONTROLLER, controller) self.assertEqual(settings.DEFAULT_ACTION, action) self.assertFalse(params) self.assertFalse(qs_params) controller, action, params, qs_params = results[1] self.assertEqual('foo', controller) self.assertEqual(settings.DEFAULT_ACTION, action) self.assertFalse(params) self.assertFalse(qs_params) controller, action, params, qs_params = results[2] self.assertEqual('foo', controller) self.assertEqual(settings.DEFAULT_ACTION, action) self.assertFalse(params) self.assertFalse(qs_params) controller, action, params, qs_params = results[3] self.assertEqual('foo', controller) self.assertEqual('bar', action) self.assertFalse(params) self.assertFalse(qs_params) controller, action, params, qs_params = results[4] self.assertEqual('foo', controller) self.assertEqual('bar', action) self.assertFalse(params) self.assertFalse(qs_params) controller, action, params, qs_params = results[5] self.assertEqual('foo', controller) self.assertEqual('bar', action) self.assertTrue('car' == params[0]) self.assertTrue('lar' == params[1]) self.assertFalse(qs_params) controller, action, params, qs_params = results[6] self.assertEqual('foo', controller) self.assertEqual('bar', action) self.assertTrue('car' == params[0]) self.assertTrue('lar' == params[1]) self.assertTrue('dar' == params[2]) self.assertFalse(qs_params) controller, action, params, qs_params = results[7] self.assertEqual('foo', controller) self.assertEqual('bar', action) self.assertEqual('car', params[0]) self.assertEqual(1, len(params)) self.assertEqual('far', qs_params['mar']) controller, action, params, qs_params = results[7] self.assertEqual('foo', controller) self.assertEqual('bar', action) self.assertEqual('car', params[0]) self.assertEqual(1, len(params)) self.assertEqual('far', qs_params['mar'])

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0.607829

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2,861

5.495177

0.157556

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0.115857

0.12639

0.797542

0.775892

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0.262845

2,861

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33.658824

0.801802

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0.067808

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null

1

0

1

0

null

0

1

0

7

3369318b83db1b6103cc4fe17e4231f370b0a190

220

py

Python

tests/examples/helper.py

897615138/tfsnippet-jill

2fc898a4def866c8d3c685168df1fa22083bb143

[ "MIT" ]

63

2018-06-06T11:56:40.000Z

2022-03-22T08:00:59.000Z

tests/examples/helper.py

897615138/tfsnippet-jill

2fc898a4def866c8d3c685168df1fa22083bb143

[ "MIT" ]

39

2018-07-04T12:40:53.000Z

2022-02-09T23:48:44.000Z

tests/examples/helper.py

897615138/tfsnippet-jill

2fc898a4def866c8d3c685168df1fa22083bb143

[ "MIT" ]

34

2018-06-25T09:59:22.000Z

2022-02-23T12:46:33.000Z

import os import unittest def skipUnlessRunExamplesTests(): return unittest.skipUnless( os.environ.get('RUN_EXAMPLES_TEST_CASE') == '1', 'RUN_EXAMPLES_TEST_CASE is not set to 1, thus skipped' )

22

62

0.7

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0.202703

0.256757

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220

9

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24.444444

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true

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null

0

1

0

1

0

7

cc031e0dcfdc07cd4c5c24c9f64562c5c65fde5c

8,766

py

Python

src/graphql/scalar_descriptors/strict/test/scalar_descriptors.py

btrekkie/graphql

6c118550267eeb57a9653f4f46d7bbd6c5902110

[ "MIT" ]

null

src/graphql/scalar_descriptors/strict/test/scalar_descriptors.py

btrekkie/graphql

6c118550267eeb57a9653f4f46d7bbd6c5902110

[ "MIT" ]

null

src/graphql/scalar_descriptors/strict/test/scalar_descriptors.py

btrekkie/graphql

6c118550267eeb57a9653f4f46d7bbd6c5902110

[ "MIT" ]

null

import unittest from graphql.scalar_descriptors.strict import GraphQlStrictBooleanDescriptor from graphql.scalar_descriptors.strict import GraphQlStrictFloatDescriptor from graphql.scalar_descriptors.strict import GraphQlStrictIdDescriptor from graphql.scalar_descriptors.strict import GraphQlStrictIntDescriptor from graphql.scalar_descriptors.strict import GraphQlStrictStringDescriptor class GraphQlStrictScalarDescriptorsTest(unittest.TestCase): """Tests scalar descriptors in graphql.scalar_descriptors.strict.""" def test_string(self): """Test GraphQlStrictStringDescriptor.""" descriptor = GraphQlStrictStringDescriptor('String') # graphql_to_python self.assertEqual('foo', descriptor.graphql_to_python('foo')) self.assertEqual('', descriptor.graphql_to_python('')) with self.assertRaises(TypeError): descriptor.graphql_to_python(None) with self.assertRaises(TypeError): descriptor.graphql_to_python(12) with self.assertRaises(TypeError): descriptor.graphql_to_python(True) with self.assertRaises(TypeError): descriptor.graphql_to_python(6.2) with self.assertRaises(TypeError): descriptor.graphql_to_python(object()) # python_to_graphql self.assertEqual('foo', descriptor.python_to_graphql('foo')) self.assertEqual('', descriptor.python_to_graphql('')) with self.assertRaises(TypeError): descriptor.python_to_graphql(None) with self.assertRaises(TypeError): descriptor.python_to_graphql(12) with self.assertRaises(TypeError): descriptor.python_to_graphql(True) with self.assertRaises(TypeError): descriptor.python_to_graphql(6.2) with self.assertRaises(TypeError): descriptor.python_to_graphql(object()) def test_id(self): """Test GraphQlStrictIdDescriptor.""" descriptor = GraphQlStrictIdDescriptor('String') # graphql_to_python self.assertEqual('foo', descriptor.graphql_to_python('foo')) self.assertEqual('', descriptor.graphql_to_python('')) self.assertEqual('12', descriptor.graphql_to_python(12)) with self.assertRaises(TypeError): descriptor.graphql_to_python(None) with self.assertRaises(TypeError): descriptor.graphql_to_python(True) with self.assertRaises(TypeError): descriptor.graphql_to_python(6.2) with self.assertRaises(TypeError): descriptor.graphql_to_python(object()) # python_to_graphql self.assertEqual('foo', descriptor.python_to_graphql('foo')) self.assertEqual('', descriptor.python_to_graphql('')) with self.assertRaises(TypeError): descriptor.python_to_graphql(None) with self.assertRaises(TypeError): descriptor.python_to_graphql(12) with self.assertRaises(TypeError): descriptor.python_to_graphql(True) with self.assertRaises(TypeError): descriptor.python_to_graphql(6.2) with self.assertRaises(TypeError): descriptor.python_to_graphql(object()) def test_int(self): """Test GraphQlStrictIntDescriptor.""" descriptor = GraphQlStrictIntDescriptor('Integer') # graphql_to_python self.assertEqual(42, descriptor.graphql_to_python(42)) self.assertEqual(-12, descriptor.graphql_to_python(-12)) self.assertEqual(0, descriptor.graphql_to_python(0)) with self.assertRaises(TypeError): descriptor.graphql_to_python(None) with self.assertRaises(TypeError): descriptor.graphql_to_python('14') with self.assertRaises(TypeError): descriptor.graphql_to_python(2.6) with self.assertRaises(TypeError): descriptor.graphql_to_python('2.6') with self.assertRaises(ValueError): descriptor.graphql_to_python(123456789012) with self.assertRaises(TypeError): descriptor.graphql_to_python(object()) # python_to_graphql self.assertEqual(42, descriptor.python_to_graphql(42)) self.assertEqual(-12, descriptor.python_to_graphql(-12)) self.assertEqual(0, descriptor.python_to_graphql(0)) with self.assertRaises(TypeError): descriptor.python_to_graphql(None) with self.assertRaises(TypeError): descriptor.python_to_graphql('14') with self.assertRaises(TypeError): descriptor.python_to_graphql(2.6) with self.assertRaises(TypeError): descriptor.python_to_graphql('2.6') with self.assertRaises(ValueError): descriptor.python_to_graphql(123456789012) with self.assertRaises(TypeError): descriptor.python_to_graphql(object()) def test_float(self): """Test GraphQlStrictFloatDescriptor.""" descriptor = GraphQlStrictFloatDescriptor('Float') # graphql_to_python self.assertEqual(42, descriptor.graphql_to_python(42)) self.assertEqual(-12, descriptor.graphql_to_python(-12)) self.assertEqual(0, descriptor.graphql_to_python(0)) self.assertTrue( descriptor.graphql_to_python(123456789123456789123456789L) in ( 123456789123456789123456789L, float(123456789123456789123456789L), )) self.assertEqual(4.3, descriptor.graphql_to_python(4.3)) self.assertEqual(-15.3, descriptor.graphql_to_python(-15.3)) self.assertEqual(1.4e28, descriptor.graphql_to_python(1.4e28)) self.assertEqual(2.6e-8, descriptor.graphql_to_python(2.6e-8)) with self.assertRaises(TypeError): descriptor.graphql_to_python(None) with self.assertRaises(TypeError): descriptor.graphql_to_python('14') with self.assertRaises(TypeError): descriptor.graphql_to_python('6.5') with self.assertRaises(TypeError): descriptor.graphql_to_python('6.5e-2') with self.assertRaises(TypeError): descriptor.graphql_to_python(object()) # python_to_graphql self.assertEqual(42, descriptor.python_to_graphql(42)) self.assertEqual(-12, descriptor.python_to_graphql(-12)) self.assertEqual(0, descriptor.python_to_graphql(0)) self.assertTrue( descriptor.python_to_graphql(123456789123456789123456789L) in ( 123456789123456789123456789L, float(123456789123456789123456789L), )) self.assertEqual(4.3, descriptor.python_to_graphql(4.3)) self.assertEqual(-15.3, descriptor.python_to_graphql(-15.3)) self.assertEqual(1.4e28, descriptor.python_to_graphql(1.4e28)) self.assertEqual(2.6e-8, descriptor.python_to_graphql(2.6e-8)) with self.assertRaises(TypeError): descriptor.python_to_graphql(None) with self.assertRaises(TypeError): descriptor.python_to_graphql('14') with self.assertRaises(TypeError): descriptor.python_to_graphql('6.5') with self.assertRaises(TypeError): descriptor.python_to_graphql('6.5e-2') with self.assertRaises(TypeError): descriptor.python_to_graphql(object()) def test_boolean(self): """Test GraphQlStrictBooleanDescriptor.""" descriptor = GraphQlStrictBooleanDescriptor('Boolean') # graphql_to_python self.assertEqual(True, descriptor.graphql_to_python(True)) self.assertEqual(False, descriptor.graphql_to_python(False)) with self.assertRaises(TypeError): descriptor.graphql_to_python(None) with self.assertRaises(TypeError): descriptor.graphql_to_python('12') with self.assertRaises(TypeError): descriptor.graphql_to_python('true') with self.assertRaises(TypeError): descriptor.graphql_to_python(42) with self.assertRaises(TypeError): descriptor.graphql_to_python(object()) # python_to_graphql self.assertEqual(True, descriptor.python_to_graphql(True)) self.assertEqual(False, descriptor.python_to_graphql(False)) with self.assertRaises(TypeError): descriptor.python_to_graphql(None) with self.assertRaises(TypeError): descriptor.python_to_graphql('12') with self.assertRaises(TypeError): descriptor.python_to_graphql('true') with self.assertRaises(TypeError): descriptor.python_to_graphql(42) with self.assertRaises(TypeError): descriptor.python_to_graphql(object())

44.050251

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0.680242

895

8,766

6.435754

0.063687

0.070833

0.177083

0.246701

0.852083

0.810764

0.769444

0.740278

0.723438

0.693576

0

0.047864

0.223021

8,766

198

77

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0.797827

0.02042

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0

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0

0.52439

0

null

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0.036585

null

0

null

0

1

0

null

0

1

0

9

cc2b09adb51ec2aee1acd64f6e0cd12b1fb97c57

217

py

Python

frontend/views.py

arnaudlimbourg/rencontres-django-2016

e7074d772791be7068f155d832c2c9265a8c9522

[ "Apache-2.0" ]

null

frontend/views.py

arnaudlimbourg/rencontres-django-2016

e7074d772791be7068f155d832c2c9265a8c9522

[ "Apache-2.0" ]

null

frontend/views.py

arnaudlimbourg/rencontres-django-2016

e7074d772791be7068f155d832c2c9265a8c9522

[ "Apache-2.0" ]

null

from django.shortcuts import render from django.http import HttpResponse from django.shortcuts import render_to_response def index(request): return render_to_response('index.html', context={"request": request})

27.125

73

0.806452

29

217

5.896552

0.517241

0.175439

0.222222

0.292398

0.362573

0

0.110599

217

7

74

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false

0

0.6

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null

0

1

0

1

0

null

0

1

0

7

cc2c132a60b55de5852b91806855d60ae07baa4d

131

py

Python

reverser/tests/reverse_test.py

devacto/python-puzzles

e92d43b950c3cc44a03b85199fc0f568a3c7b70b

[ "MIT" ]

null

reverser/tests/reverse_test.py

devacto/python-puzzles

e92d43b950c3cc44a03b85199fc0f568a3c7b70b

[ "MIT" ]

null

reverser/tests/reverse_test.py

devacto/python-puzzles

e92d43b950c3cc44a03b85199fc0f568a3c7b70b

[ "MIT" ]

null

from nose.tools import assert_equal from reverser import reverse def test_return(): assert_equal(reverse.reverse("go"), "og")

21.833333

45

0.763359

19

131

5.105263

0.684211

0.226804

0

0.129771

131

5

46

26.2

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0

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true

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null

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1

0

1

0

1

0

8

cc2fb183652bb56a016f46cedd017dfb565ced91

16,602

py

Python

tests/test_mapping.py

oarepo/invenio-oarepo-multilingual

03d382c152aa44f2912c13b225adb418dbf48109

[ "MIT" ]

null

tests/test_mapping.py

oarepo/invenio-oarepo-multilingual

03d382c152aa44f2912c13b225adb418dbf48109

[ "MIT" ]

3

2020-08-30T18:00:00.000Z

2021-08-05T16:34:28.000Z

tests/test_mapping.py

oarepo/oarepo-multilingual

03d382c152aa44f2912c13b225adb418dbf48109

[ "MIT" ]

4

2020-08-20T11:18:40.000Z

2021-03-24T10:53:40.000Z

# -*- coding: utf-8 -*- # # Copyright (C) 2019 CESNET. # # Invenio OpenID Connect is free software; you can redistribute it and/or modify it # under the terms of the MIT License; see LICENSE file for more details. from flask import Flask from oarepo_multilingual.mapping.mapping_handler import handler def test_mapping(): """Simple test of mapping.""" app = Flask('testapp') app.config.update(ELASTICSEARCH_DEFAULT_LANGUAGE_TEMPLATE={ "type": "text", "fields": { "raw": { "type": "keyword" } } }) app.config.update(MULTILINGUAL_SUPPORTED_LANGUAGES=["cs", "en", "_"]) assert handler(app=app) == { 'type': 'object', 'properties': { 'cs': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } }, 'en': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } }, '_': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } } } } app.config.update(MULTILINGUAL_SUPPORTED_LANGUAGES=["_"]) assert handler(app=app) == { 'type': 'object', 'properties': { '_': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } } } } app.config.update(MULTILINGUAL_SUPPORTED_LANGUAGES=["cs", "_"]) assert handler(app=app) == { 'type': 'object', 'properties': { 'cs': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } }, '_': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } } } } app.config.update(MULTILINGUAL_SUPPORTED_LANGUAGES=["cs", "en", "_"]) app.config.update(ELASTICSEARCH_LANGUAGE_TEMPLATES={ "cs": { "type": "text", "fields": { "raw": { "type": "text" } } }, "en": { "type": "text", "fields": { "raw": { "type": "text" } } }, '_': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } } } ) assert handler(app=app) == { 'type': 'object', 'properties': { 'cs': { "type": "text", "fields": { "raw": { "type": "text" } } }, 'en': { "type": "text", "fields": { "raw": { "type": "text" } } }, '_': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } } } } app.config.update(MULTILINGUAL_SUPPORTED_LANGUAGES=["cs", "en", "_"]) app.config.update(ELASTICSEARCH_LANGUAGE_TEMPLATES={ "cs": { "type": "text", "fields": { "raw": { "type": "text" } } } } ) assert handler(app=app) == { 'type': 'object', 'properties': { 'cs': { "type": "text", "fields": { "raw": { "type": "text" } } }, 'en': { "type": "text", "fields": { "raw": { "type": "keyword" } } }, '_': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } } } } app.config.update(MULTILINGUAL_SUPPORTED_LANGUAGES=["en", "_"]) app.config.update(ELASTICSEARCH_LANGUAGE_TEMPLATES={ "_": { "type": "text", "fields": { "raw": { "type": "text" } } } } ) assert handler(app=app) == { 'type': 'object', 'properties': { 'en': { "type": "text", "fields": { "raw": { "type": "keyword" } } }, '_': { 'type': 'text', 'fields': { "raw": { "type": "text" } } } } } def test_ids(): app = Flask('testapp') app.config.update(MULTILINGUAL_SUPPORTED_LANGUAGES=["cs", "_"]) app.config.update(ELASTICSEARCH_LANGUAGE_TEMPLATES={ "cs#context": { "type": "text", "fields": { "raw": { "type": "text" }, "jej": {"type": "text"} } }, "cs": { "type": "text", "fields": { "raw": { "type": "text" } } } } ) assert handler(app=app, id='context') == { 'type': 'object', 'properties': { 'cs': { "type": "text", "fields": { "raw": { "type": "text" }, "jej": {"type": "text"} } }, '_': {} } } app.config.update(MULTILINGUAL_SUPPORTED_LANGUAGES=["cs", "en", "_"]) app.config.update(ELASTICSEARCH_LANGUAGE_TEMPLATES={ "cs#context": { "type": "text", "fields": { "raw": { "type": "text" }, "jej": {"type": "text"} } }, "cs": { "type": "text", "fields": { "raw": { "type": "keyword" } } }, "en": { "type": "text", "fields": { "raw": { "type": "keyword" } } }, "_#context": { "type": "text", "fields": { "raw": { "type": "text" } } } } ) assert handler(app=app, id='context') == { 'type': 'object', 'properties': { 'cs': { 'type': 'text', 'fields': { "raw": { "type": "text" }, "jej": {"type": "text"} } }, 'en': { 'type': 'text', 'fields': { "raw": { "type": "keyword" } } }, '_': { 'type': 'text', 'fields': { "raw": { "type": "text" } } } } } def test_all_languages(): app = Flask('testapp') app.config.update( MULTILINGUAL_SUPPORTED_LANGUAGES=['cs', 'en', 'sk', 'de', 'fr', 'ru', 'es', 'nl', 'it', 'no', 'pl', 'da', 'el', 'hu', 'lt', 'pt', 'bg', 'ro', 'sv']) app.config.update(ELASTICSEARCH_LANGUAGE_TEMPLATES={ "*#context": { "type": "text", "copy_to": "field.*", "fields": { "raw": { "type": "keyword" } } } } ) assert handler(app=app, id='context') == { 'properties': { 'bg': { 'copy_to': 'field.bg', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'cs': { 'copy_to': 'field.cs', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'da': { 'copy_to': 'field.da', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'de': { 'copy_to': 'field.de', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'el': { 'copy_to': 'field.el', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'en': { 'copy_to': 'field.en', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'es': { 'copy_to': 'field.es', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'fr': { 'copy_to': 'field.fr', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'hu': { 'copy_to': 'field.hu', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'it': { 'copy_to': 'field.it', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'lt': { 'copy_to': 'field.lt', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'nl': { 'copy_to': 'field.nl', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'no': { 'copy_to': 'field.no', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'pl': { 'copy_to': 'field.pl', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'pt': { 'copy_to': 'field.pt', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'ro': { 'copy_to': 'field.ro', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'ru': { 'copy_to': 'field.ru', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'sk': { 'copy_to': 'field.sk', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'sv': { 'copy_to': 'field.sv', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' } }, 'type': 'object' } def test_all_languages_2(): app = Flask('testapp') app.config.update( MULTILINGUAL_SUPPORTED_LANGUAGES=['cs', 'en', 'sk', 'de', 'fr', 'ru', 'es', 'nl', 'it', 'no', 'pl', 'da', 'el', 'hu', 'lt', 'pt', 'bg', 'ro', 'sv']) app.config.update(ELASTICSEARCH_LANGUAGE_TEMPLATES={ "*#context": { "type": "text", "copy_to": "field", "fields": { "raw": { "type": "keyword" } } } } ) assert handler(app=app, id='context') == { 'properties': { 'bg': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'cs': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'da': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'de': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'el': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'en': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'es': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'fr': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'hu': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'it': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'lt': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'nl': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'no': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'pl': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'pt': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'ro': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'ru': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'sk': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' }, 'sv': { 'copy_to': 'field', 'fields': {'raw': {'type': 'keyword'}}, 'type': 'text' } }, 'type': 'object' }

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null

0

9

0bf2b853d3118e51c5623bc226ae8cfe7e939b90

116

py

Python

platform/hwconf_data/efm32jg1b/PythonSnippet/__init__.py

lenloe1/v2.7

9ac9c4a7bb37987af382c80647f42d84db5f2e1d

[ "Zlib" ]

null

platform/hwconf_data/efm32jg1b/PythonSnippet/__init__.py

lenloe1/v2.7

9ac9c4a7bb37987af382c80647f42d84db5f2e1d

[ "Zlib" ]

1

2020-08-25T02:36:22.000Z

platform/hwconf_data/efm32jg1b/PythonSnippet/__init__.py

lenloe1/v2.7

9ac9c4a7bb37987af382c80647f42d84db5f2e1d

[ "Zlib" ]

1

2020-08-25T01:56:04.000Z

from efm32jg1b.halconfig import halconfig_types as types from efm32jg1b.halconfig import halconfig_dependency as dep

58

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8

042cd755802e520db226530a880c6a76ded1f0b7

14,137

py

Python

experiments/WebsiteFingerprinting/Bento-DF/DeepFingerprint-changes/utility.py

rajKarra69420/bento

1324189e26acfe3a372882519bd78e037d93997c

[ "BSD-3-Clause" ]

3

2021-12-01T02:11:15.000Z

2022-02-03T22:45:00.000Z

experiments/WebsiteFingerprinting/Bento-DF/DeepFingerprint-changes/utility.py

rajKarra69420/bento

1324189e26acfe3a372882519bd78e037d93997c

[ "BSD-3-Clause" ]

4

2021-11-27T11:04:36.000Z

2022-02-17T02:53:21.000Z

experiments/WebsiteFingerprinting/Bento-DF/DeepFingerprint-changes/utility.py

rajKarra69420/bento

1324189e26acfe3a372882519bd78e037d93997c

[ "BSD-3-Clause" ]

5

2021-07-01T20:23:43.000Z

2022-03-12T18:10:34.000Z

import pickle as pickle import numpy as np # Load data for non-defended dataset for CW setting def LoadDataBentoCW(): print("[BENTO] Loading non-defended dataset for closed-world scenario") # Point to the directory storing data dataset_dir = '../dataset/ClosedWorld/BentoBrowser/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_train_VANILLA.pkl', 'rb') as handle: X_train = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_train_VANILLA.pkl', 'rb') as handle: y_train = np.array(pickle.load(handle, encoding='latin1')) # Load validation data with open(dataset_dir + 'X_valid_VANILLA.pkl', 'rb') as handle: X_valid = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_valid_VANILLA.pkl', 'rb') as handle: y_valid = np.array(pickle.load(handle, encoding='latin1')) # Load testing data with open(dataset_dir + 'X_test_VANILLA.pkl', 'rb') as handle: X_test = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_test_VANILLA.pkl', 'rb') as handle: y_test = np.array(pickle.load(handle, encoding='latin1')) print("Data dimensions:") print("X: Training data's shape : ", X_train.shape) print("y: Training data's shape : ", y_train.shape) print("X: Validation data's shape : ", X_valid.shape) print("y: Validation data's shape : ", y_valid.shape) print("X: Testing data's shape : ", X_test.shape) print("y: Testing data's shape : ", y_test.shape) return X_train, y_train, X_valid, y_valid, X_test, y_test # Load data for non-defended dataset for CW setting def LoadDataNoDefCW(): print("Loading non-defended dataset for closed-world scenario") # Point to the directory storing data dataset_dir = 'D:/ClosedWorld/NoDef/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_train_NoDef.pkl', 'rb') as handle: X_train = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_train_NoDef.pkl', 'rb') as handle: y_train = np.array(pickle.load(handle, encoding='latin1')) # Load validation data with open(dataset_dir + 'X_valid_NoDef.pkl', 'rb') as handle: X_valid = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_valid_NoDef.pkl', 'rb') as handle: y_valid = np.array(pickle.load(handle, encoding='latin1')) # Load testing data with open(dataset_dir + 'X_test_NoDef.pkl', 'rb') as handle: X_test = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_test_NoDef.pkl', 'rb') as handle: y_test = np.array(pickle.load(handle, encoding='latin1')) print("Data dimensions:") print("X: Training data's shape : ", X_train.shape) print("y: Training data's shape : ", y_train.shape) print("X: Validation data's shape : ", X_valid.shape) print("y: Validation data's shape : ", y_valid.shape) print("X: Testing data's shape : ", X_test.shape) print("y: Testing data's shape : ", y_test.shape) return X_train, y_train, X_valid, y_valid, X_test, y_test # Load data for non-defended dataset for CW setting def LoadDataWTFPADCW(): print("Loading WTF-PAD dataset for closed-world scenario") # Point to the directory storing data dataset_dir = 'D:/ClosedWorld/WTFPAD/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_train_WTFPAD.pkl', 'rb') as handle: X_train = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_train_WTFPAD.pkl', 'rb') as handle: y_train = np.array(pickle.load(handle, encoding='latin1')) # Load validation data with open(dataset_dir + 'X_valid_WTFPAD.pkl', 'rb') as handle: X_valid = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_valid_WTFPAD.pkl', 'rb') as handle: y_valid = np.array(pickle.load(handle, encoding='latin1')) # Load testing data with open(dataset_dir + 'X_test_WTFPAD.pkl', 'rb') as handle: X_test = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_test_WTFPAD.pkl', 'rb') as handle: y_test = np.array(pickle.load(handle, encoding='latin1')) print("Data dimensions:") print("X: Training data's shape : ", X_train.shape) print("y: Training data's shape : ", y_train.shape) print("X: Validation data's shape : ", X_valid.shape) print("y: Validation data's shape : ", y_valid.shape) print("X: Testing data's shape : ", X_test.shape) print("y: Testing data's shape : ", y_test.shape) return X_train, y_train, X_valid, y_valid, X_test, y_test # Load data for non-defended dataset for CW setting def LoadDataWalkieTalkieCW(): print("Loading Walkie-Talkie dataset for closed-world scenario") # Point to the directory storing data dataset_dir = 'D:/ClosedWorld/WalkieTalkie/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_train_WalkieTalkie.pkl', 'rb') as handle: X_train = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_train_WalkieTalkie.pkl', 'rb') as handle: y_train = np.array(pickle.load(handle, encoding='latin1')) # Load validation data with open(dataset_dir + 'X_valid_WalkieTalkie.pkl', 'rb') as handle: X_valid = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_valid_WalkieTalkie.pkl', 'rb') as handle: y_valid = np.array(pickle.load(handle, encoding='latin1')) # Load testing data with open(dataset_dir + 'X_test_WalkieTalkie.pkl', 'rb') as handle: X_test = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_test_WalkieTalkie.pkl', 'rb') as handle: y_test = np.array(pickle.load(handle, encoding='latin1')) print("Data dimensions:") print("X: Training data's shape : ", X_train.shape) print("y: Training data's shape : ", y_train.shape) print("X: Validation data's shape : ", X_valid.shape) print("y: Validation data's shape : ", y_valid.shape) print("X: Testing data's shape : ", X_test.shape) print("y: Testing data's shape : ", y_test.shape) return X_train, y_train, X_valid, y_valid, X_test, y_test # Load data for non-defended dataset for OW training def LoadDataNoDefOW_Training(): print("Loading non-defended dataset for open-world scenario for training") # Point to the directory storing data dataset_dir = '../dataset/OpenWorld/NoDef/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_train_NoDef.pkl', 'rb') as handle: X_train = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_train_NoDef.pkl', 'rb') as handle: y_train = np.array(pickle.load(handle, encoding='latin1')) # Load validation data with open(dataset_dir + 'X_valid_NoDef.pkl', 'rb') as handle: X_valid = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_valid_NoDef.pkl', 'rb') as handle: y_valid = np.array(pickle.load(handle, encoding='latin1')) print("Data dimensions:") print("X: Training data's shape : ", X_train.shape) print("y: Training data's shape : ", y_train.shape) print("X: Validation data's shape : ", X_valid.shape) print("y: Validation data's shape : ", y_valid.shape) return X_train, y_train, X_valid, y_valid # Load data for non-defended dataset for OW evaluation def LoadDataNoDefOW_Evaluation(): print("Loading non-defended dataset for open-world scenario for evaluation") # Point to the directory storing data dataset_dir = '../dataset/OpenWorld/NoDef/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_test_Mon_NoDef.pkl', 'rb') as handle: X_test_Mon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'y_test_Mon_NoDef.pkl', 'rb') as handle: y_test_Mon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'X_test_Unmon_NoDef.pkl', 'rb') as handle: X_test_Unmon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'y_test_Unmon_NoDef.pkl', 'rb') as handle: y_test_Unmon = pickle.load(handle, encoding='latin1') X_test_Mon = np.array(X_test_Mon) y_test_Mon = np.array(y_test_Mon) X_test_Unmon = np.array(X_test_Unmon) y_test_Unmon = np.array(y_test_Unmon) return X_test_Mon, y_test_Mon, X_test_Unmon, y_test_Unmon # Load data for WTF-PAD dataset for OW training def LoadDataWTFPADOW_Training(): print("Loading WTF-PAD dataset for open-world scenario for training") # Point to the directory storing data dataset_dir = '../dataset/OpenWorld/WTFPAD/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_train_WTFPAD.pkl', 'rb') as handle: X_train = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_train_WTFPAD.pkl', 'rb') as handle: y_train = np.array(pickle.load(handle, encoding='latin1')) # Load validation data with open(dataset_dir + 'X_valid_WTFPAD.pkl', 'rb') as handle: X_valid = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_valid_WTFPAD.pkl', 'rb') as handle: y_valid = np.array(pickle.load(handle, encoding='latin1')) print("Data dimensions:") print("X: Training data's shape : ", X_train.shape) print("y: Training data's shape : ", y_train.shape) print("X: Validation data's shape : ", X_valid.shape) print("y: Validation data's shape : ", y_valid.shape) return X_train, y_train, X_valid, y_valid # Load data for WTF-PAD dataset for OW evaluation def LoadDataWTFPADOW_Evaluation(): print("Loading WTF-PAD dataset for open-world scenario for evaluation") # Point to the directory storing data dataset_dir = '../dataset/OpenWorld/WTFPAD/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_test_Mon_WTFPAD.pkl', 'rb') as handle: X_test_Mon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'y_test_Mon_WTFPAD.pkl', 'rb') as handle: y_test_Mon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'X_test_Unmon_WTFPAD.pkl', 'rb') as handle: X_test_Unmon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'y_test_Unmon_WTFPAD.pkl', 'rb') as handle: y_test_Unmon = pickle.load(handle, encoding='latin1') X_test_Mon = np.array(X_test_Mon) y_test_Mon = np.array(y_test_Mon) X_test_Unmon = np.array(X_test_Unmon) y_test_Unmon = np.array(y_test_Unmon) return X_test_Mon, y_test_Mon, X_test_Unmon, y_test_Unmon # Load data for WalkieTalkie dataset for OW training def LoadDataWalkieTalkieOW_Training(): print("Loading Walkie-Talkie dataset for open-world scenario for training") # Point to the directory storing data dataset_dir = '../dataset/OpenWorld/WalkieTalkie/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_train_WalkieTalkie.pkl', 'rb') as handle: X_train = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_train_WalkieTalkie.pkl', 'rb') as handle: y_train = np.array(pickle.load(handle, encoding='latin1')) # Load validation data with open(dataset_dir + 'X_valid_WalkieTalkie.pkl', 'rb') as handle: X_valid = np.array(pickle.load(handle, encoding='latin1')) with open(dataset_dir + 'y_valid_WalkieTalkie.pkl', 'rb') as handle: y_valid = np.array(pickle.load(handle, encoding='latin1')) print("Data dimensions:") print("X: Training data's shape : ", X_train.shape) print("y: Training data's shape : ", y_train.shape) print("X: Validation data's shape : ", X_valid.shape) print("y: Validation data's shape : ", y_valid.shape) return X_train, y_train, X_valid, y_valid # Load data for WTF-PAD dataset for OW evaluation def LoadDataWalkieTalkieOW_Evaluation(): print("Loading Walkie-Talkie dataset for open-world scenario for evaluation") # Point to the directory storing data dataset_dir = '../dataset/OpenWorld/WalkieTalkie/' # X represents a sequence of traffic directions # y represents a sequence of corresponding label (website's label) # Load training data with open(dataset_dir + 'X_test_Mon_WalkieTalkie.pkl', 'rb') as handle: X_test_Mon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'y_test_Mon_WalkieTalkie.pkl', 'rb') as handle: y_test_Mon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'X_test_Unmon_WalkieTalkie.pkl', 'rb') as handle: X_test_Unmon = pickle.load(handle, encoding='latin1') with open(dataset_dir + 'y_test_Unmon_WalkieTalkie.pkl', 'rb') as handle: y_test_Unmon = pickle.load(handle, encoding='latin1') X_test_Mon = np.array(X_test_Mon) y_test_Mon = np.array(y_test_Mon) X_test_Unmon = np.array(X_test_Unmon) y_test_Unmon = np.array(y_test_Unmon) return X_test_Mon, y_test_Mon, X_test_Unmon, y_test_Unmon

42.581325

81

0.693499

2,088

14,137

4.515326

0.037356

0.061519

0.076368

0.091642

0.967331

0.961179

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0.937102

0.932541

0.931799

0

0.004175

0.186744

14,137

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42.70997

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false

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0.274611

0

null

0

1

0

1

0

null

0

7

04350c4f2add71af542bd93194b95079383f7e08

912

py

Python

popcorn_gallery/popcorn/search_indexes.py

Koenkk/popcorn_maker

0978b9f98dacd4e8eb753404b24eb584f410aa11

[ "BSD-3-Clause" ]

15

2015-03-23T02:55:20.000Z

2021-01-12T12:42:30.000Z

popcorn_gallery/popcorn/search_indexes.py

Koenkk/popcorn_maker

0978b9f98dacd4e8eb753404b24eb584f410aa11

[ "BSD-3-Clause" ]

null

popcorn_gallery/popcorn/search_indexes.py

Koenkk/popcorn_maker

0978b9f98dacd4e8eb753404b24eb584f410aa11

[ "BSD-3-Clause" ]

16

2015-02-18T21:43:31.000Z

2021-11-09T22:50:03.000Z

from haystack import indexes from .models import Project, Template class TemplateIndex(indexes.SearchIndex, indexes.Indexable): text = indexes.CharField(document=True, use_template=True) name = indexes.CharField(model_attr='name') description = indexes.CharField(model_attr='description') def get_model(self): return Template def index_queryset(self): """Used when the entire index for model is updated.""" return self.get_model().live.all() class ProjectIndex(indexes.SearchIndex, indexes.Indexable): text = indexes.CharField(document=True, use_template=True) name = indexes.CharField(model_attr='name') description = indexes.CharField(model_attr='description') def get_model(self): return Project def index_queryset(self): """Used when the entire index for model is updated.""" return self.get_model().live.all()

30.4

62

0.712719

111

912

5.747748

0.324324

0.15047

0.131661

0.15674

0.833856

0

0.182018

912

29

63

31.448276

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0.666667

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0

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0.222222

false

0

0.111111

1

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null

0

1

0

null

0

1

0

1

0

8

f0930cab7a2e83fc1db5cbdc16994a8879d56e2b

178

py

Python

site-root/change_loadout_name.py

TED-996/krait-twostones

51b27793b9cd536d680fb9a6785c57473d35cac1

[ "MIT" ]

null

site-root/change_loadout_name.py

TED-996/krait-twostones

51b27793b9cd536d680fb9a6785c57473d35cac1

[ "MIT" ]

null

site-root/change_loadout_name.py

TED-996/krait-twostones

51b27793b9cd536d680fb9a6785c57473d35cac1

[ "MIT" ]

null

from ctrl import change_loadout_name import krait import logging logging.debug("Got in pagina rutabila change_loadout_name ") krait.response = change_loadout_name.get_response()

29.666667

60

0.848315

26

178

5.538462

0.576923

0.270833

0.354167

0

0.095506

178

6

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29.666667

0.89441

0

0.240223

0

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true

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0.6

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0.6

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1

0

null

0

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1

0

1

0

7

f0dc32771f05024b2b093d992f62a714d7ce8afa

191

py

Python

djangoratings/exceptions.py

gelo-zhukov/django-ratings

fb5495d7a9a3aec9800f12dff58803ff68a4c753

[ "BSD-2-Clause" ]

68

2015-02-06T17:04:59.000Z

2021-11-26T14:43:46.000Z

djangoratings/exceptions.py

conorsheehan/django-ratings

ecc051df5096d57044e038a8ffa1504dea1acbbe

[ "BSD-2-Clause" ]

13

2020-02-18T09:57:52.000Z

2022-01-13T02:12:04.000Z

djangoratings/exceptions.py

conorsheehan/django-ratings

ecc051df5096d57044e038a8ffa1504dea1acbbe

[ "BSD-2-Clause" ]

58

2015-01-06T09:37:07.000Z

2022-03-02T22:37:36.000Z

class InvalidRating(ValueError): pass class AuthRequired(TypeError): pass class CannotChangeVote(Exception): pass class CannotDeleteVote(Exception): pass class IPLimitReached(Exception): pass

38.2

39

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191

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9bd7a404e1975638a7f2736cb4c6fe13c222fc46

6,658

py

Python

tests/utils.py

originalpkbims/subgrounds-pkbims

03271135d985bc4a53129edb0cb2391555012270

[ "Apache-2.0" ]

null

tests/utils.py

originalpkbims/subgrounds-pkbims

03271135d985bc4a53129edb0cb2391555012270

[ "Apache-2.0" ]

null

tests/utils.py

originalpkbims/subgrounds-pkbims

03271135d985bc4a53129edb0cb2391555012270

[ "Apache-2.0" ]

null

from subgrounds.schema import ( TypeMeta, SchemaMeta, TypeRef, # input_value_of_argument ) from subgrounds.subgraph import Subgraph def schema(): return SchemaMeta(query_type='Query', type_map={ 'Int': TypeMeta.ScalarMeta('Int', ''), 'Float': TypeMeta.ScalarMeta('Float', ''), 'BigInt': TypeMeta.ScalarMeta('BigInt', ''), 'BigDecimal': TypeMeta.ScalarMeta('BigDecimal', ''), 'String': TypeMeta.ScalarMeta('String', ''), 'OrderDirection': TypeMeta.EnumMeta('OrderDirection', '', [ TypeMeta.EnumValueMeta('asc', ''), TypeMeta.EnumValueMeta('desc', '') ]), 'Query': TypeMeta.ObjectMeta('Query', '', fields=[ TypeMeta.FieldMeta('pairs', '', [ TypeMeta.ArgumentMeta('first', '', TypeRef.Named('Int'), None), TypeMeta.ArgumentMeta('where', '', TypeRef.Named('Pair_filter'), None), TypeMeta.ArgumentMeta('orderBy', '', TypeRef.Named('Pair_orderBy'), None), TypeMeta.ArgumentMeta('orderDirection', '', TypeRef.Named('OrderDirection'), None), ], TypeRef.non_null_list('Pair')), TypeMeta.FieldMeta('swaps', '', [], TypeRef.non_null_list('Swap')), ]), 'Swap': TypeMeta.ObjectMeta('Swap', '', fields=[ TypeMeta.FieldMeta('id', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('timestamp', '', [], TypeRef.Named('BigInt')), TypeMeta.FieldMeta('amount0In', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('amount0Out', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('amount1In', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('amount1Out', '', [], TypeRef.Named('BigDecimal')), ]), 'Token': TypeMeta.ObjectMeta('Token', '', fields=[ TypeMeta.FieldMeta('id', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('name', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('symbol', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('decimals', '', [], TypeRef.Named('Int')), ]), 'Pair': TypeMeta.ObjectMeta('Pair', '', fields=[ TypeMeta.FieldMeta('id', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('token0', '', [], TypeRef.Named('Token')), TypeMeta.FieldMeta('token1', '', [], TypeRef.Named('Token')), TypeMeta.FieldMeta('reserveUSD', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('priceToken0', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('priceToken1', '', [], TypeRef.Named('BigDecimal')), ]), 'Pair_filter': TypeMeta.InputObjectMeta('Pair_filter', '', [ TypeMeta.ArgumentMeta('token0', '', TypeRef.Named('String'), None), TypeMeta.ArgumentMeta('token1', '', TypeRef.Named('String'), None), TypeMeta.ArgumentMeta('reserveUSD_lt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('reserveUSD_gt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('priceToken0_lt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('priceToken0_gt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('priceToken1_lt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('priceToken1_gt', '', TypeRef.Named('BigDecimal'), None), ]), 'Pair_orderBy': TypeMeta.EnumMeta('Pair_orderBy', '', [ TypeMeta.EnumValueMeta('id', ''), TypeMeta.EnumValueMeta('reserveUSD', '') ]) }) def subgraph(): return Subgraph("", SchemaMeta(query_type='Query', type_map={ 'Int': TypeMeta.ScalarMeta('Int', ''), 'Float': TypeMeta.ScalarMeta('Float', ''), 'BigInt': TypeMeta.ScalarMeta('BigInt', ''), 'BigDecimal': TypeMeta.ScalarMeta('BigDecimal', ''), 'String': TypeMeta.ScalarMeta('String', ''), 'OrderDirection': TypeMeta.EnumMeta('OrderDirection', '', [ TypeMeta.EnumValueMeta('asc', ''), TypeMeta.EnumValueMeta('desc', '') ]), 'Query': TypeMeta.ObjectMeta('Query', '', fields=[ TypeMeta.FieldMeta('pairs', '', [ TypeMeta.ArgumentMeta('first', '', TypeRef.Named('Int'), None), TypeMeta.ArgumentMeta('where', '', TypeRef.Named('Pair_filter'), None), TypeMeta.ArgumentMeta('orderBy', '', TypeRef.Named('Pair_orderBy'), None), TypeMeta.ArgumentMeta('orderDirection', '', TypeRef.Named('OrderDirection'), None), ], TypeRef.non_null_list('Pair')), TypeMeta.FieldMeta('swaps', '', [], TypeRef.non_null_list('Swap')), ]), 'Swap': TypeMeta.ObjectMeta('Swap', '', fields=[ TypeMeta.FieldMeta('id', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('timestamp', '', [], TypeRef.Named('BigInt')), TypeMeta.FieldMeta('amount0In', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('amount0Out', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('amount1In', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('amount1Out', '', [], TypeRef.Named('BigDecimal')), ]), 'Token': TypeMeta.ObjectMeta('Token', '', fields=[ TypeMeta.FieldMeta('id', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('name', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('symbol', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('decimals', '', [], TypeRef.Named('Int')), ]), 'Pair': TypeMeta.ObjectMeta('Pair', '', fields=[ TypeMeta.FieldMeta('id', '', [], TypeRef.Named('String')), TypeMeta.FieldMeta('token0', '', [], TypeRef.Named('Token')), TypeMeta.FieldMeta('token1', '', [], TypeRef.Named('Token')), TypeMeta.FieldMeta('reserveUSD', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('priceToken0', '', [], TypeRef.Named('BigDecimal')), TypeMeta.FieldMeta('priceToken1', '', [], TypeRef.Named('BigDecimal')), ]), 'Pair_filter': TypeMeta.InputObjectMeta('Pair_filter', '', [ TypeMeta.ArgumentMeta('token0', '', TypeRef.Named('String'), None), TypeMeta.ArgumentMeta('token1', '', TypeRef.Named('String'), None), TypeMeta.ArgumentMeta('reserveUSD_lt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('reserveUSD_gt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('priceToken0_lt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('priceToken0_gt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('priceToken1_lt', '', TypeRef.Named('BigDecimal'), None), TypeMeta.ArgumentMeta('priceToken1_gt', '', TypeRef.Named('BigDecimal'), None), ]), 'Pair_orderBy': TypeMeta.EnumMeta('Pair_orderBy', '', [ TypeMeta.EnumValueMeta('id', ''), TypeMeta.EnumValueMeta('reserveUSD', '') ]) })) def identity(x): return x

51.215385

91

0.627966

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7.092466

0.111301

0.16224

0.138098

0.075326

0.961371

0

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0.150345

6,658

129

92

51.612403

0.727241

0.003454

0

0.885246

0

0.20594

0

1

0.02459

false

0

0.016393

0.02459

0.065574

0

null

0

1

0

1

0

null

0

7

9be2afaee3c59ffa976d24db903f71f737d209d8

42,509

py

Python

ArcPy/ModeloBooleano.py

phporath/GIS-Tools

5a1613dfcd516ae1194dd4f1d3981ed11aa0dfa7

[ "MIT" ]

null

ArcPy/ModeloBooleano.py

phporath/GIS-Tools

5a1613dfcd516ae1194dd4f1d3981ed11aa0dfa7

[ "MIT" ]

null

ArcPy/ModeloBooleano.py

phporath/GIS-Tools

5a1613dfcd516ae1194dd4f1d3981ed11aa0dfa7

[ "MIT" ]

null

# -*- coding: utf-8 -*- # --------------------------------------------------------------------------- # ModeloBooleano.py # Created on: 2019-10-22 10:43:58.00000 # (generated by ArcGIS/ModelBuilder) # Description: # --------------------------------------------------------------------------- # Set the necessary product code # import arcinfo # Import arcpy module import arcpy # Check out any necessary licenses arcpy.CheckOutExtension("spatial") # Load required toolboxes arcpy.ImportToolbox("C:/Users/phpor/Documents/UFSC/Dissertação/ModelBuilder/01_ModelBuilder/FerramentaDissertacao.tbx") # Local variables: Hidrografia = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\hidrografia.shp" Massa_dagua = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\techoMassaDagua.shp" Nascentes = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\nascenteRio.shp" Área_de_estudo = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\areaEstudo.shp" raster = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\GDB\\Modelagem.gdb" terraIndigena_shp = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\terraIndigena.shp" Sítio_arqueológico = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\sitiosArquelogicos.shp" Área_Edificada = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\areaEdificada.shp" setorRisco_shp = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\setorRisco.shp" linhaTransmissao_shp = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\linhaTransmissao.shp" Output_Coordinate_System = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" mangue_shp = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\mangue.shp" vetor = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\GDB\\Modelagem.gdb\\BOL_vetor" Mask_Mosaico_MDT = "%raster%\\mosaico_MDT_extractbymask" Slope_Mosaico_MDT = "%raster%\\mosaico_MDT_slope" APP_Margem_Rio_10m_Pol = "%vetor%\\bol_APP_margem_rio_10m_pol" Buffer_APP_Margem_de_Rio__10m__Pol = "%vetor%\\bol_APP_margem_rio_10m_buffer_pol" bol_app_merge_Dissolve = "%vetor%\\bol_app_merge_Dissolve" Adição_de_informação = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\areaEstudo.shp" Clip_APP = "%vetor%\\bol_APP_clip" APP_Margem_de_Rio__10m_ = "%vetor%\\bol_APP_margem_rio_10m" APP_Nascente = "%vetor%\\bol_nascentes" Adição_campo = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\areaEstudo.shp" Erase_APP = "%vetor%\\bol_APP_erase" Merge_APP = "%vetor%\\bol_APP_merge" Adição_campo_Booelana__5_ = "%vetor%\\bol_APP_merge" Raster_MDT = "%raster%\\mosaico_MDT_reclassify" bol_APP_dissolve = "%vetor%\\bol_APP_dissolve" Raster_APP = "%raster%\\bol_APP" BOL_result = "%vetor%\\BOL_result" APP_Margem_Rio_10_a_50_m_Pol = "%vetor%\\bol_APP_margem_rio_10a50m_pol" Buffer_APP_Margem_Rio_10_a_50_m_Pol = "%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer" APP_Margem_Rio_50_a_200_m_Pol = "%vetor%\\bol_APP_margem_rio_50a200m_pol" Buffer_APP_Margem_Rio_50_a_200_m_Pol = "%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer" Clip_Terra_Indígena = "%vetor%\\bol_ti_clip" Erase_Terra_Indígena = "%vetor%\\bol_ti_erase" Merge_Terra_Indígena = "%vetor%\\bol_ti_merge" Adição_campo_Booelana__8_ = "%vetor%\\bol_ti_merge" bol_ti_dissolve = "%vetor%\\bol_ti_dissolve" Raster_Terra_Indígena = "%raster%\\bol_ti" Sitio_Arqueológico = "%vetor%\\bol_sitio_arqueologico" Clip_Sítio_Arqueológico = "%vetor%\\bol_sitio_arqueologico_clip" Erase_Terra_Indígena__2_ = "%vetor%\\bol_sitio_arqueologico_erase" Merge_Sítio_Arqueológico = "%vetor%\\bol_sitio_arqueologico_merge" Adição_campo_Booelana__9_ = "%vetor%\\bol_sitio_arqueologico_merge" bol_sitio_arqueologico_dissolve = "%vetor%\\bol_sitio_arqueologico_dissolve" Raster_Sítio_Arqueológico = "%raster%\\bol_sitio_arqueologico" Erase_Área_Edificada = "%vetor%\\bol_area_edificada_erase" Merge_Área_Edificada = "%vetor%\\bol_area_edificada_merge" Adição_campo_Booelana__10_ = "%vetor%\\bol_area_edificada_merge" bol_area_edificada_dissolve = "%vetor%\\bol_area_edificada_dissolve" Raster_Área_Edificada = "%raster%\\bol_area_edificada" Buffer_LT = "%vetor%\\SHP\\bol_lt" Clip_LT = "%vetor%\\bol_lt_clip" Erase_LT = "%vetor%\\bol_lt_erase" Merge_LT = "%vetor%\\bol_lt_merge" Adição_campo_Booelana__11_ = "%vetor%\\bol_lt_merge" bol_lt_dissolve = "%vetor%\\bol_lt_dissolve" Raster_LT = "%raster%\\bol_lt" Clip_Setor_de_Risco = "%vetor%\\bol_setor_risco_clip" Erase_Setor_de_Risco = "%vetor%\\bol_setor_risco_erase" Merge_Setor_de_Risco = "%vetor%\\bol_setor_risco_merge" Adição_campo_Booelana__12_ = "%vetor%\\bol_setor_risco_merge" bol_setor_risco_dissolve = "%vetor%\\bol_setor_risco_dissolve" Raster_Setor_de_Risco = "%raster%\\bol_setor_risco" Output_Values__2_ = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\Raster\\MDT\\MDT_SG-22-Z-D-II-3-NE-D.tif" mosaico_MDT = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\GDB\\Modelagem.gdb\\mosaico_MDT" Parâmetros_Booleanos__12_ = "%vetor%\\bol_setor_risco_merge" Adição_campo_PorcArea = "%vetor%\\bol_setor_risco_merge" Parâmetros_Booleanos__7_ = "%vetor%\\bol_setor_risco_merge" Parâmetros_Booleanos__8_ = "%vetor%\\bol_ti_merge" Adição_campo_PorcArea__2_ = "%vetor%\\bol_ti_merge" Parâmetros_Booleanos__13_ = "%vetor%\\bol_ti_merge" Parâmetros_Booleanos__11_ = "%vetor%\\bol_lt_merge" Adição_campo_PorcArea__3_ = "%vetor%\\bol_lt_merge" Parâmetros_Booleanos__14_ = "%vetor%\\bol_lt_merge" Parâmetros_Booleanos__9_ = "%vetor%\\bol_sitio_arqueologico_merge" Adição_campo_PorcArea__7_ = "%vetor%\\bol_sitio_arqueologico_merge" Parâmetros_Booleanos__18_ = "%vetor%\\bol_sitio_arqueologico_merge" Parâmetros_Booleanos__5_ = "%vetor%\\bol_APP_merge" Adição_campo_PorcArea__9_ = "%vetor%\\bol_APP_merge" Parâmetros_Booleanos__20_ = "%vetor%\\bol_APP_merge" Parâmetros_Booleanos__10_ = "%vetor%\\bol_area_edificada_merge" Adição_campo_PorcArea__10_ = "%vetor%\\bol_area_edificada_merge" Parâmetros_Booleanos__21_ = "%vetor%\\bol_area_edificada_merge" Merge_APP_2 = "%vetor%\\bol_app_merge" APP_declividade = "%vetor%\\APP_declividade" # Process: Add Field (7) arcpy.AddField_management(Área_de_estudo, "Aestudo", "TEXT", "2", "", "5", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (7) arcpy.CalculateField_management(Adição_campo, "Aestudo", "\"Sim\"", "PYTHON", "") # Process: Select (2) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Select_analysis(Massa_dagua, APP_Margem_Rio_10m_Pol, "\"largura\" = 'Até 10m'") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Buffer (3) arcpy.Buffer_analysis(APP_Margem_Rio_10m_Pol, Buffer_APP_Margem_de_Rio__10m__Pol, "30 Meters", "FULL", "ROUND", "ALL", "") # Process: Select (3) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Select_analysis(Massa_dagua, APP_Margem_Rio_10_a_50_m_Pol, "\"largura\" = '10 a 50m'") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Buffer (2) arcpy.Buffer_analysis(APP_Margem_Rio_10_a_50_m_Pol, Buffer_APP_Margem_Rio_10_a_50_m_Pol, "50 Meters", "FULL", "ROUND", "ALL", "") # Process: Buffer (7) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Buffer_analysis(Nascentes, APP_Nascente, "50 Meters", "FULL", "ROUND", "ALL", "") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Select (4) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Select_analysis(Massa_dagua, APP_Margem_Rio_50_a_200_m_Pol, "\"largura\" = '50 a 200m'") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Buffer (4) arcpy.Buffer_analysis(APP_Margem_Rio_50_a_200_m_Pol, Buffer_APP_Margem_Rio_50_a_200_m_Pol, "100 Meters", "FULL", "ROUND", "ALL", "") # Process: Buffer (6) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Buffer_analysis(Hidrografia, APP_Margem_de_Rio__10m_, "30 Meters", "FULL", "ROUND", "ALL", "") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Analise Booleana Itarador Raster arcpy.gp.toolbox = "C:/Users/phpor/Documents/UFSC/Dissertação/ModelBuilder/01_ModelBuilder/FerramentaDissertacao.tbx"; # Warning: the toolbox C:/Users/phpor/Documents/UFSC/Dissertação/ModelBuilder/01_ModelBuilder/FerramentaDissertacao.tbx DOES NOT have an alias. # Please assign this toolbox an alias to avoid tool name collisions # And replace arcpy.gp.AnaliseBooleanaItaradorRaster(...) with arcpy.AnaliseBooleanaItaradorRaster_ALIAS(...) arcpy.gp.AnaliseBooleanaItaradorRaster() # Process: Mosaic To New Raster arcpy.MosaicToNewRaster_management(Output_Values__2_, raster, "mosaico_MDT", Output_Coordinate_System, "32_BIT_SIGNED", "", "1", "MAXIMUM", "MATCH") # Process: Extract by Mask arcpy.gp.ExtractByMask_sa(mosaico_MDT, Área_de_estudo, Mask_Mosaico_MDT) # Process: Slope arcpy.gp.Slope_sa(Mask_Mosaico_MDT, Slope_Mosaico_MDT, "PERCENT_RISE", "1") # Process: Reclassify (2) arcpy.gp.Reclassify_sa(Slope_Mosaico_MDT, "Value", "0 100 NODATA;100 1500 0", Raster_MDT, "DATA") # Process: Raster to Polygon tempEnvironment0 = arcpy.env.workspace arcpy.env.workspace = "C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\GDB\\Modelagem.gdb\\BOL_vetor" arcpy.RasterToPolygon_conversion(Raster_MDT, APP_declividade, "NO_SIMPLIFY", "VALUE") arcpy.env.workspace = tempEnvironment0 # Process: Merge (6) arcpy.Merge_management("%vetor%\\bol_APP_margem_rio_10m_buffer_pol;%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer;%vetor%\\bol_nascentes;%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer;%vetor%\\bol_APP_margem_rio_10m;%vetor%\\APP_declividade;C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\mangue.shp", Merge_APP_2, "Id \"Id\" true true false 6 Long 0 6 ,First,#,%vetor%\\APP_declividade,ID,-1,-1,%vetor%\\bol_APP_margem_rio_10m,ID,-1,-1;app \"app\" true true false 50 Text 0 0 ,First,#,C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\mangue.shp,app,-1,-1;Shape_Leng \"Shape_Leng\" false true true 0 Double 0 0 ,First,#,%vetor%\\APP_declividade,Shape_Length,-1,-1;Shape_Area \"Shape_Area\" false true true 0 Double 0 0 ,First,#,%vetor%\\APP_declividade,Shape_Area,-1,-1,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,Shape_area,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,Shape_area,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,Shape_area,-1,-1;GRIDCODE \"GRIDCODE\" true true false 0 Long 0 0 ,First,#,%vetor%\\APP_declividade,GRIDCODE,-1,-1;NOME \"NOME\" true true false 80 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,NOME,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,NOME,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,NOME,-1,-1;GEOMETRIAA \"GEOMETRIAA\" true true false 9 Long 0 9 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,GEOMETRIAA,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,GEOMETRIAA,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,GEOMETRIAA,-1,-1;REGIME \"REGIME\" true true false 9 Long 0 9 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,REGIME,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,REGIME,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,REGIME,-1,-1;NOMEABREV \"NOMEABREV\" true true false 50 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,NOMEABREV,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,NOMEABREV,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,NOMEABREV,-1,-1;ID_TRECHO_ \"ID_TRECHO_\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,ID_TRECHO_,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,ID_TRECHO_,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,ID_TRECHO_,-1,-1;TIPOTRECHO \"TIPOTRECHO\" true true false 9 Long 0 9 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,TIPOTRECHO,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,TIPOTRECHO,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,TIPOTRECHO,-1,-1;SALINIDADE \"SALINIDADE\" true true false 9 Long 0 9 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,SALINIDADE,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,SALINIDADE,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,SALINIDADE,-1,-1;largura \"largura\" true true false 15 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,largura,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,largura,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,largura,-1,-1;Shape_le_1 \"Shape_le_1\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,Shape_length,-1,-1;BUFF_DIST \"BUFF_DIST\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10a50m_pol_buffer,BUFF_DIST,-1,-1,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,BUFF_DIST,-1,-1,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,BUFF_DIST,-1,-1,%vetor%\\bol_APP_margem_rio_10m,BUFF_DIST,-1,-1,%vetor%\\bol_nascentes,BUFF_DIST,-1,-1;Shape_le_2 \"Shape_le_2\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m_buffer_pol,Shape_length,-1,-1;Shape_le_3 \"Shape_le_3\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_50a200m_pol_buffer,Shape_length,-1,-1;COTRECHO \"COTRECHO\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,COTRECHO,-1,-1;COCURSODAG \"COCURSODAG\" true true false 50 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,COCURSODAG,-1,-1,%vetor%\\bol_nascentes,COCURSODAG,-1,-1;COBACIA \"COBACIA\" true true false 50 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,COBACIA,-1,-1;CORIO \"CORIO\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,CORIO,-1,-1;CODOM \"CODOM\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,CODOM,-1,-1;DEDOMINIAL \"DEDOMINIAL\" true true false 50 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,DEDOMINIAL,-1,-1;NUCOMPTREC \"NUCOMPTREC\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUCOMPTREC,-1,-1;NUDISTBACT \"NUDISTBACT\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUDISTBACT,-1,-1;NUDISTCDAG \"NUDISTCDAG\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUDISTCDAG,-1,-1;NUAREACONT \"NUAREACONT\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUAREACONT,-1,-1;NUAREAMONT \"NUAREAMONT\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUAREAMONT,-1,-1;NUNIVOTTO \"NUNIVOTTO\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUNIVOTTO,-1,-1;DEDIREC \"DEDIREC\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,DEDIREC,-1,-1;DECORPODAG \"DECORPODAG\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,DECORPODAG,-1,-1;DELIGACAO \"DELIGACAO\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,DELIGACAO,-1,-1;NORIO \"NORIO\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NORIO,-1,-1;NORIOCOMP \"NORIOCOMP\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NORIOCOMP,-1,-1;NUCOMPRIO \"NUCOMPRIO\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUCOMPRIO,-1,-1;NUDISTBACR \"NUDISTBACR\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUDISTBACR,-1,-1;COCDADESAG \"COCDADESAG\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,COCDADESAG,-1,-1;NUCOMPCDA \"NUCOMPCDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUCOMPCDA,-1,-1;NUTRJUS \"NUTRJUS\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUTRJUS,-1,-1;NUTRMON \"NUTRMON\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUTRMON,-1,-1;NUTRAFL \"NUTRAFL\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUTRAFL,-1,-1;NUDISTBACC \"NUDISTBACC\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUDISTBACC,-1,-1;NUAREABACC \"NUAREABACC\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUAREABACC,-1,-1;NUORDEMCDA \"NUORDEMCDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUORDEMCDA,-1,-1;NUNIVOTCDA \"NUNIVOTCDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NUNIVOTCDA,-1,-1;NULONDETRE \"NULONDETRE\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULONDETRE,-1,-1;NULATDETRE \"NULATDETRE\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULATDETRE,-1,-1;NULONPATRE \"NULONPATRE\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULONPATRE,-1,-1;NULATPATRE \"NULATPATRE\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULATPATRE,-1,-1;NULONDECDA \"NULONDECDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULONDECDA,-1,-1,%vetor%\\bol_nascentes,NULONDECDA,-1,-1;NULATDECDA \"NULATDECDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULATDECDA,-1,-1,%vetor%\\bol_nascentes,NULATDECDA,-1,-1;NULONPACDA \"NULONPACDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULONPACDA,-1,-1;NULATPACDA \"NULATPACDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULATPACDA,-1,-1;NULONDERIO \"NULONDERIO\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULONDERIO,-1,-1;NULATDERIO \"NULATDERIO\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULATDERIO,-1,-1;NULONPARIO \"NULONPARIO\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULONPARIO,-1,-1;NULATPARIO \"NULATPARIO\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,NULATPARIO,-1,-1;DTVERSAO \"DTVERSAO\" true true false 50 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,DTVERSAO,-1,-1,%vetor%\\bol_nascentes,DTVERSAO,-1,-1;poligono \"poligono\" true true false 3 Text 0 0 ,First,#,%vetor%\\bol_APP_margem_rio_10m,poligono,-1,-1;OBJECTID \"OBJECTID\" true true false 9 Long 0 9 ,First,#,%vetor%\\bol_nascentes,OBJECTID,-1,-1;CONOCDA \"CONOCDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_nascentes,CONOCDA,-1,-1;COCDA \"COCDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_nascentes,COCDA,-1,-1;COCDACOSTA \"COCDACOSTA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_nascentes,COCDACOSTA,-1,-1;CONASCDA \"CONASCDA\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_nascentes,CONASCDA,-1,-1") # Process: Dissolve (4) arcpy.Dissolve_management(Merge_APP_2, bol_app_merge_Dissolve, "", "", "MULTI_PART", "DISSOLVE_LINES") # Process: Clip (4) arcpy.Clip_analysis(bol_app_merge_Dissolve, Adição_de_informação, Clip_APP, "") # Process: Erase (5) arcpy.Erase_analysis(Adição_de_informação, Clip_APP, Erase_APP, "") # Process: Merge (5) arcpy.Merge_management("%vetor%\\bol_APP_erase;%vetor%\\bol_APP_clip", Merge_APP, "nome \"nome\" true true false 40 Text 0 0 ,First,#,%vetor%\\bol_APP_erase,nome,-1,-1;fonte \"fonte\" true true false 20 Text 0 0 ,First,#,%vetor%\\bol_APP_erase,fonte,-1,-1;Aestudo \"Aestudo\" true true false 5 Text 0 0 ,First,#,%vetor%\\bol_APP_erase,Aestudo,-1,-1;area \"area\" true true false 13 Float 0 0 ,First,#,%vetor%\\bol_APP_erase,area,-1,-1;Shape_length \"Shape_length\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_APP_erase,Shape_length,-1,-1;Shape_area \"Shape_area\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_APP_erase,Shape_area,-1,-1") # Process: Add Field (9) arcpy.AddField_management(Merge_APP, "Booleana", "SHORT", "2", "", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (9) arcpy.CalculateField_management(Adição_campo_Booelana__5_, "Booleana", "Classify ( !Aestudo! )", "PYTHON", "def Classify(booleana):\\n if (booleana == 'Sim'):\\n return 1\\n else:\\n return 0") # Process: Add Field (21) arcpy.AddField_management(Parâmetros_Booleanos__5_, "PorcArea", "FLOAT", "7", "5", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (21) arcpy.CalculateField_management(Adição_campo_PorcArea__9_, "PorcArea", "(!Shape.area@squaremeters!*100)/318725000", "PYTHON", "") # Process: Dissolve (9) arcpy.Dissolve_management(Parâmetros_Booleanos__20_, bol_APP_dissolve, "Booleana", "PorcArea SUM", "MULTI_PART", "DISSOLVE_LINES") # Process: Feature to Raster (8) arcpy.FeatureToRaster_conversion(bol_APP_dissolve, "Booleana", Raster_APP, "5") # Process: Clip (6) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Clip_analysis(terraIndigena_shp, Adição_de_informação, Clip_Terra_Indígena, "") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Erase (7) arcpy.Erase_analysis(Adição_de_informação, Clip_Terra_Indígena, Erase_Terra_Indígena, "") # Process: Merge (7) arcpy.Merge_management("%vetor%\\bol_ti_clip;%vetor%\\bol_ti_erase", Merge_Terra_Indígena, "idTerraInd \"idTerraInd\" true true false 9 Long 0 9 ,First,#,%vetor%\\bol_ti_clip,idTerraInd,-1,-1;codFunai \"codFunai\" true true false 9 Long 0 9 ,First,#,%vetor%\\bol_ti_clip,codFunai,-1,-1;nome \"nome\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,nome,-1,-1,%vetor%\\bol_ti_erase,nome,-1,-1;etnia \"etnia\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,etnia,-1,-1;municipio \"municipio\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,municipio,-1,-1;uf \"uf\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,uf,-1,-1;superficie \"superficie\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_ti_clip,superficie,-1,-1;fase_ti \"fase_ti\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,fase_ti,-1,-1;modalidade \"modalidade\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,modalidade,-1,-1;reestudo \"reestudo\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,reestudo,-1,-1;coordRegio \"coordRegio\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,coordRegio,-1,-1;fonte \"fonte\" true true false 50 Text 0 0 ,First,#,%vetor%\\bol_ti_clip,fonte,-1,-1,%vetor%\\bol_ti_erase,fonte,-1,-1;area \"area\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_ti_clip,area,-1,-1,%vetor%\\bol_ti_erase,area,-1,-1;Shape_leng \"Shape_leng\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_ti_clip,Shape_length,-1,-1;Shape_area \"Shape_area\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_ti_clip,Shape_area,-1,-1,%vetor%\\bol_ti_erase,Shape_area,-1,-1;Aestudo \"Aestudo\" true true false 5 Text 0 0 ,First,#,%vetor%\\bol_ti_erase,Aestudo,-1,-1;Shape_length \"Shape_length\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_ti_erase,Shape_length,-1,-1") # Process: Add Field (8) arcpy.AddField_management(Merge_Terra_Indígena, "Booleana", "SHORT", "2", "", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (8) arcpy.CalculateField_management(Adição_campo_Booelana__8_, "Booleana", "Classify ( !Aestudo! )", "PYTHON", "def Classify(booleana):\\n if (booleana == 'Sim'):\\n return 1\\n else:\\n return 0") # Process: Add Field (14) arcpy.AddField_management(Parâmetros_Booleanos__8_, "PorcArea", "FLOAT", "7", "5", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (14) arcpy.CalculateField_management(Adição_campo_PorcArea__2_, "PorcArea", "(!Shape.area@squaremeters!*100)/318725000", "PYTHON", "") # Process: Dissolve (2) arcpy.Dissolve_management(Parâmetros_Booleanos__13_, bol_ti_dissolve, "Booleana", "PorcArea SUM", "MULTI_PART", "DISSOLVE_LINES") # Process: Feature to Raster (7) arcpy.FeatureToRaster_conversion(bol_ti_dissolve, "Booleana", Raster_Terra_Indígena, "5") # Process: Buffer (5) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Buffer_analysis(Sítio_arqueológico, Sitio_Arqueológico, "50 Meters", "FULL", "ROUND", "ALL", "") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Clip (9) arcpy.Clip_analysis(Sitio_Arqueológico, Adição_de_informação, Clip_Sítio_Arqueológico, "") # Process: Erase (8) arcpy.Erase_analysis(Adição_de_informação, Clip_Sítio_Arqueológico, Erase_Terra_Indígena__2_, "") # Process: Merge (8) arcpy.Merge_management("%vetor%\\bol_sitio_arqueologico_clip;%vetor%\\bol_sitio_arqueologico_erase", Merge_Sítio_Arqueológico, "nome \"nome\" true true false 40 Text 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_clip,nome,-1,-1,%vetor%\\bol_sitio_arqueologico_erase,nome,-1,-1;Shape_Area \"Shape_Area\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_clip,Shape_area,-1,-1,%vetor%\\bol_sitio_arqueologico_erase,Shape_area,-1,-1;cnsa \"cnsa\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_clip,cnsa,-1,-1;município \"município\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_clip,município,-1,-1;uf \"uf\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_clip,uf,-1,-1;BUFF_DIST \"BUFF_DIST\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_clip,BUFF_DIST,-1,-1;Shape_le_1 \"Shape_le_1\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_clip,Shape_length,-1,-1;fonte \"fonte\" true true false 20 Text 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_erase,fonte,-1,-1;Aestudo \"Aestudo\" true true false 5 Text 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_erase,Aestudo,-1,-1;area \"area\" true true false 13 Float 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_erase,area,-1,-1;Shape_length \"Shape_length\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_sitio_arqueologico_erase,Shape_length,-1,-1") # Process: Add Field (10) arcpy.AddField_management(Merge_Sítio_Arqueológico, "Booleana", "SHORT", "2", "", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (10) arcpy.CalculateField_management(Adição_campo_Booelana__9_, "Booleana", "Classify ( !Aestudo! )", "PYTHON", "def Classify(booleana):\\n if (booleana == 'Sim'):\\n return 1\\n else:\\n return 0") # Process: Add Field (19) arcpy.AddField_management(Parâmetros_Booleanos__9_, "PorcArea", "FLOAT", "7", "5", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (19) arcpy.CalculateField_management(Adição_campo_PorcArea__7_, "PorcArea", "(!Shape.area@squaremeters!*100)/318725000", "PYTHON", "") # Process: Dissolve (7) arcpy.Dissolve_management(Parâmetros_Booleanos__18_, bol_sitio_arqueologico_dissolve, "Booleana", "PorcArea SUM", "MULTI_PART", "DISSOLVE_LINES") # Process: Feature to Raster (9) arcpy.FeatureToRaster_conversion(bol_sitio_arqueologico_dissolve, "Booleana", Raster_Sítio_Arqueológico, "5") # Process: Erase (9) arcpy.Erase_analysis(Adição_de_informação, Área_Edificada, Erase_Área_Edificada, "") # Process: Merge (9) arcpy.Merge_management("%vetor%\\bol_area_edificada_erase;C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\areaEdificada.shp", Merge_Área_Edificada, "id \"id\" true true false 4 Short 0 4 ,First,#,C:\\Users\\phpor\\Documents\\UFSC\\Dissertação\\Dados_georreferenciados\\SHP\\areaEdificada.shp,id,-1,-1;nome \"nome\" true true false 40 Text 0 0 ,First,#,%vetor%\\bol_area_edificada_erase,nome,-1,-1;fonte \"fonte\" true true false 20 Text 0 0 ,First,#,%vetor%\\bol_area_edificada_erase,fonte,-1,-1;Aestudo \"Aestudo\" true true false 5 Text 0 0 ,First,#,%vetor%\\bol_area_edificada_erase,Aestudo,-1,-1;area \"area\" true true false 13 Float 0 0 ,First,#,%vetor%\\bol_area_edificada_erase,area,-1,-1;Shape_length \"Shape_length\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_area_edificada_erase,Shape_length,-1,-1;Shape_area \"Shape_area\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_area_edificada_erase,Shape_area,-1,-1") # Process: Add Field (11) arcpy.AddField_management(Merge_Área_Edificada, "Booleana", "SHORT", "2", "", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (11) arcpy.CalculateField_management(Adição_campo_Booelana__10_, "Booleana", "Classify ( !Aestudo! )", "PYTHON", "def Classify(booleana):\\n if (booleana == 'Sim'):\\n return 1\\n else:\\n return 0") # Process: Add Field (22) arcpy.AddField_management(Parâmetros_Booleanos__10_, "PorcArea", "FLOAT", "7", "5", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (22) arcpy.CalculateField_management(Adição_campo_PorcArea__10_, "PorcArea", "(!Shape.area@squaremeters!*100)/318725000", "PYTHON", "") # Process: Dissolve (10) arcpy.Dissolve_management(Parâmetros_Booleanos__21_, bol_area_edificada_dissolve, "Booleana", "PorcArea SUM", "MULTI_PART", "DISSOLVE_LINES") # Process: Feature to Raster (10) arcpy.FeatureToRaster_conversion(bol_area_edificada_dissolve, "Booleana", Raster_Área_Edificada, "5") # Process: Buffer (8) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Buffer_analysis(linhaTransmissao_shp, Buffer_LT, "buffer", "FULL", "ROUND", "ALL", "") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Clip (10) arcpy.Clip_analysis(Buffer_LT, Adição_de_informação, Clip_LT, "") # Process: Erase (10) arcpy.Erase_analysis(Adição_de_informação, Clip_LT, Erase_LT, "") # Process: Merge (10) arcpy.Merge_management("%vetor%\\bol_lt_clip;%vetor%\\bol_lt_erase", Merge_LT, "Shape_Leng \"Shape_Leng\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_lt_clip,Shape_Leng,-1,-1;Shape_Area \"Shape_Area\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_lt_clip,Shape_area,-1,-1,%vetor%\\bol_lt_erase,Shape_area,-1,-1;osm_id \"osm_id\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,osm_id,-1,-1;name \"name\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,name,-1,-1;highway \"highway\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,highway,-1,-1;waterway \"waterway\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,waterway,-1,-1;aerialway \"aerialway\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,aerialway,-1,-1;barrier \"barrier\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,barrier,-1,-1;man_made \"man_made\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,man_made,-1,-1;z_order \"z_order\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_lt_clip,z_order,-1,-1;other_tags \"other_tags\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,other_tags,-1,-1;tensao \"tensao\" true true false 50 Text 0 0 ,First,#,%vetor%\\bol_lt_clip,tensao,-1,-1;buffer \"buffer\" true true false 13 Float 0 0 ,First,#,%vetor%\\bol_lt_clip,buffer,-1,-1;BUFF_DIST \"BUFF_DIST\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_lt_clip,BUFF_DIST,-1,-1;Shape_le_1 \"Shape_le_1\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_lt_clip,Shape_length,-1,-1;nome \"nome\" true true false 40 Text 0 0 ,First,#,%vetor%\\bol_lt_erase,nome,-1,-1;fonte \"fonte\" true true false 20 Text 0 0 ,First,#,%vetor%\\bol_lt_erase,fonte,-1,-1;Aestudo \"Aestudo\" true true false 5 Text 0 0 ,First,#,%vetor%\\bol_lt_erase,Aestudo,-1,-1;area \"area\" true true false 13 Float 0 0 ,First,#,%vetor%\\bol_lt_erase,area,-1,-1;Shape_length \"Shape_length\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_lt_erase,Shape_length,-1,-1") # Process: Add Field (12) arcpy.AddField_management(Merge_LT, "Booleana", "SHORT", "2", "", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (12) arcpy.CalculateField_management(Adição_campo_Booelana__11_, "Booleana", "Classify ( !Aestudo! )", "PYTHON", "def Classify(booleana):\\n if (booleana == 'Sim'):\\n return 1\\n else:\\n return 0") # Process: Add Field (15) arcpy.AddField_management(Parâmetros_Booleanos__11_, "PorcArea", "FLOAT", "7", "5", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (15) arcpy.CalculateField_management(Adição_campo_PorcArea__3_, "PorcArea", "(!Shape.area@squaremeters!*100)/318725000", "PYTHON", "") # Process: Dissolve (3) arcpy.Dissolve_management(Parâmetros_Booleanos__14_, bol_lt_dissolve, "Booleana", "PorcArea SUM", "MULTI_PART", "DISSOLVE_LINES") # Process: Feature to Raster (11) arcpy.FeatureToRaster_conversion(bol_lt_dissolve, "Booleana", Raster_LT, "5") # Process: Clip (11) tempEnvironment0 = arcpy.env.outputCoordinateSystem arcpy.env.outputCoordinateSystem = "PROJCS['SIRGAS_2000_UTM_Zone_22S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-51.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]]" arcpy.Clip_analysis(setorRisco_shp, Adição_de_informação, Clip_Setor_de_Risco, "") arcpy.env.outputCoordinateSystem = tempEnvironment0 # Process: Erase (11) arcpy.Erase_analysis(Adição_de_informação, Clip_Setor_de_Risco, Erase_Setor_de_Risco, "") # Process: Merge (11) arcpy.Merge_management("%vetor%\\bol_setor_risco_erase;%vetor%\\bol_setor_risco_clip", Merge_Setor_de_Risco, "Shape_Area \"Shape_Area\" true true false 19 Double 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,Shape_area,-1,-1,%vetor%\\bol_setor_risco_erase,Shape_area,-1,-1;Name \"Name\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,Name,-1,-1;UF \"UF\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,UF,-1,-1;MUNIC \"MUNIC\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,MUNIC,-1,-1;LOCAL \"LOCAL\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,LOCAL,-1,-1;DATA_SETOR \"DATA_SETOR\" true true false 8 Date 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,DATA_SETOR,-1,-1;NUM_SETOR \"NUM_SETOR\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,NUM_SETOR,-1,-1;TIPOLO_G1 \"TIPOLO_G1\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_G1,-1,-1;TIPOLO_E1 \"TIPOLO_E1\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_E1,-1,-1;COBRADE_1 \"COBRADE_1\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,COBRADE_1,-1,-1;TIPOLO_G2 \"TIPOLO_G2\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_G2,-1,-1;TIPOLO_E2 \"TIPOLO_E2\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_E2,-1,-1;COBRADE_2 \"COBRADE_2\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,COBRADE_2,-1,-1;TIPOLO_G3 \"TIPOLO_G3\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_G3,-1,-1;TIPOLO_E3 \"TIPOLO_E3\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_E3,-1,-1;COBRADE_3 \"COBRADE_3\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,COBRADE_3,-1,-1;TIPOLO_G4 \"TIPOLO_G4\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_G4,-1,-1;TIPOLO_E4 \"TIPOLO_E4\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_E4,-1,-1;COBRADE_4 \"COBRADE_4\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,COBRADE_4,-1,-1;TIPOLO_G5 \"TIPOLO_G5\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_G5,-1,-1;TIPOLO_E5 \"TIPOLO_E5\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,TIPOLO_E5,-1,-1;COBRADE_5 \"COBRADE_5\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,COBRADE_5,-1,-1;SITUACAO \"SITUACAO\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,SITUACAO,-1,-1;DESCRICAO \"DESCRICAO\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,DESCRICAO,-1,-1;NUM_MORAD \"NUM_MORAD\" true true false 19 Double 6 18 ,First,#,%vetor%\\bol_setor_risco_clip,NUM_MORAD,-1,-1;NUM_PESS \"NUM_PESS\" true true false 19 Double 6 18 ,First,#,%vetor%\\bol_setor_risco_clip,NUM_PESS,-1,-1;OBS_OCUP \"OBS_OCUP\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,OBS_OCUP,-1,-1;GRAU_VULNE \"GRAU_VULNE\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,GRAU_VULNE,-1,-1;GRAU_RISCO \"GRAU_RISCO\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,GRAU_RISCO,-1,-1;ORGAO_EXEC \"ORGAO_EXEC\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,ORGAO_EXEC,-1,-1;PROJETO \"PROJETO\" true true false 254 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,PROJETO,-1,-1;UTME \"UTME\" true true false 19 Double 6 18 ,First,#,%vetor%\\bol_setor_risco_clip,UTME,-1,-1;UTMN \"UTMN\" true true false 19 Double 6 18 ,First,#,%vetor%\\bol_setor_risco_clip,UTMN,-1,-1;ZONA \"ZONA\" true true false 19 Double 6 18 ,First,#,%vetor%\\bol_setor_risco_clip,ZONA,-1,-1;Shape_le_1 \"Shape_le_1\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_setor_risco_clip,Shape_length,-1,-1;nome \"nome\" true true false 40 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_erase,nome,-1,-1;fonte \"fonte\" true true false 20 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_erase,fonte,-1,-1;Aestudo \"Aestudo\" true true false 5 Text 0 0 ,First,#,%vetor%\\bol_setor_risco_erase,Aestudo,-1,-1;area \"area\" true true false 13 Float 0 0 ,First,#,%vetor%\\bol_setor_risco_erase,area,-1,-1;Shape_length \"Shape_length\" true true false 0 Double 0 0 ,First,#,%vetor%\\bol_setor_risco_erase,Shape_length,-1,-1") # Process: Add Field (13) arcpy.AddField_management(Merge_Setor_de_Risco, "Booleana", "SHORT", "2", "", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (13) arcpy.CalculateField_management(Adição_campo_Booelana__12_, "Booleana", "Classify ( !Aestudo! )", "PYTHON", "def Classify(booleana):\\n if (booleana == 'Sim'):\\n return 1\\n else:\\n return 0") # Process: Add Field (5) arcpy.AddField_management(Parâmetros_Booleanos__12_, "PorcArea", "FLOAT", "7", "5", "", "", "NULLABLE", "NON_REQUIRED", "") # Process: Calculate Field (5) arcpy.CalculateField_management(Adição_campo_PorcArea, "PorcArea", "(!Shape.area@squaremeters!*100)/318725000", "PYTHON", "") # Process: Dissolve arcpy.Dissolve_management(Parâmetros_Booleanos__7_, bol_setor_risco_dissolve, "Booleana", "PorcArea SUM", "MULTI_PART", "DISSOLVE_LINES") # Process: Feature to Raster (12) arcpy.FeatureToRaster_conversion(bol_setor_risco_dissolve, "Booleana", Raster_Setor_de_Risco, "5") # Process: Raster Calculator arcpy.gp.RasterCalculator_sa("\"%Raster APP%\"*\"%Raster Terra Indígena%\"*\"%Raster Sítio Arqueológico%\"*\"%Raster Área Edificada%\"*\"%Raster LT%\"*\"%Raster Setor de Risco%\"", BOL_result)

115.513587

9,052

0.76158

6,556

42,509

4.638652

0.060403

0.071027

0.069679

0.059189

0.772714

0.72385

0.65598

0.618263

0.593765

0.547401

0

0.067275

0.068809

42,509

367

9,053

115.828338

0.70099

0.058905

0

0.138462

1

0.923077

0.71022

0.527973

0

1

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false

0

0.010256

0

0.010256

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null

0

1

0

1

0

1

null

0

7

50380aa12d66188dbec0f5b56c942206d5d2fcb9

2,069

py

Python

challenges/hashmap-tree-intersection/tests/test_hashmap_tree_intersection.py

odai1990/data-structures-and-algorithms

fde43d7bdb241f6ef8de7018edab7e741b65cf77

[ "MIT" ]

null

challenges/hashmap-tree-intersection/tests/test_hashmap_tree_intersection.py

odai1990/data-structures-and-algorithms

fde43d7bdb241f6ef8de7018edab7e741b65cf77

[ "MIT" ]

1

2021-06-13T19:18:34.000Z

challenges/hashmap-tree-intersection/tests/test_hashmap_tree_intersection.py

odai1990/data-structures-and-algorithms

fde43d7bdb241f6ef8de7018edab7e741b65cf77

[ "MIT" ]

null

from hashmap_tree_intersection import __version__ from hashmap_tree_intersection.tree import BinarySearchTree from hashmap_tree_intersection.tree_intersection import TreeIntersection def test_version(): assert __version__ == '0.1.0' def test_happy_case(): tree1 = BinarySearchTree() tree1.add(10) tree1.add(5) tree1.add(6) tree2 = BinarySearchTree() tree2.add(1) tree2.add(5) tree2.add(2) test=TreeIntersection(1024) expected=test.tree_intersection(tree1,tree2) actual=[5] assert expected==actual def test_no_match(): tree1 = BinarySearchTree() tree1.add(10) tree1.add(4) tree1.add(6) tree2 = BinarySearchTree() tree2.add(1) tree2.add(5) tree2.add(2) test=TreeIntersection(1024) expected=test.tree_intersection(tree1,tree2) actual=[] assert expected==actual def test_array_long_than_other(): tree1 = BinarySearchTree() tree1.add(10) tree1.add(4) tree1.add(6) tree1.add(5) tree1.add(44) tree1.add(655) tree2 = BinarySearchTree() tree2.add(1) tree2.add(5) tree2.add(2) test=TreeIntersection(1024) expected=test.tree_intersection(tree1,tree2) actual=[5] assert expected==actual def test_array_long_than_other_and_have_repeted_number_in_same_array(): tree1 = BinarySearchTree() tree1.add(10) tree1.add(4) tree1.add(6) tree1.add(5) tree1.add(5) tree1.add(6) tree2 = BinarySearchTree() tree2.add(3) tree2.add(5) tree2.add(10) test=TreeIntersection(1024) expected=test.tree_intersection(tree1,tree2) actual=[10,5] assert expected==actual def test_other_solution(): tree1 = BinarySearchTree() tree1.add(10) tree1.add(4) tree1.add(6) tree1.add(5) tree1.add(5) tree1.add(6) tree2 = BinarySearchTree() tree2.add(3) tree2.add(5) tree2.add(10) test=TreeIntersection(1024) expected=test.tree_intersection_without_hashtabke(tree1,tree2) actual=[10,5] assert expected==actual

20.89899

72

0.675689

270

2,069

5.014815

0.162963

0.141802

0.046529

0.062038

0.836041

0.790251

0.785081

0.762186

0.716396

0.669867

0

0.08486

0.208313

2,069

98

73

21.112245

0.741758

0

0.822785

0

0.002419

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1

0.075949

false

0

0.037975

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0.113924

0

null

0

1

0

1

0

null

0

7

ace6e531c391cf4ecdf7fac9ae397d66dfb9bf8e

192

py

Python

tests/test_parametrizer.py

davidemoro/parametrizer

e5fe3b6276d30b41402b24fac61520b8e5e198a0

[ "Apache-2.0" ]

null

tests/test_parametrizer.py

davidemoro/parametrizer

e5fe3b6276d30b41402b24fac61520b8e5e198a0

[ "Apache-2.0" ]

2

2019-03-14T12:41:32.000Z

2019-03-14T12:45:21.000Z

tests/test_parametrizer.py

davidemoro/parametrizer

e5fe3b6276d30b41402b24fac61520b8e5e198a0

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- def test_parametrizer(): """ Test parametrizer """ from parametrizer import Parametrizer assert Parametrizer({'foo': 'bar'}).parametrize('$foo') == 'bar'

24

68

0.630208

19

192

6.315789

0.631579

0.266667

0

0.006329

0.177083

192

7

69

27.428571

0.753165

0.213542

0

0.090278

0

0.333333

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

1

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1

0

null

0

1

0

1

0

1

0

7

acee645e5356ce0ffa6439fdc5199b2ac38bbbe1

38

py

Python

spea/minimum_clique_cover/__init__.py

heyaroom/spea_echo

fd05285aaa55d358bde4458cc73f4e3d39058b68

[ "MIT" ]

null

spea/minimum_clique_cover/__init__.py

heyaroom/spea_echo

fd05285aaa55d358bde4458cc73f4e3d39058b68

[ "MIT" ]

null

spea/minimum_clique_cover/__init__.py

heyaroom/spea_echo

fd05285aaa55d358bde4458cc73f4e3d39058b68

[ "MIT" ]

null

from .clique_cover import clique_cover

38

0.894737

6

38

5.333333

0.666667

0.6875

0

0.078947

38

1

38

0.914286

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

acf09d8942761ce92a838957e1011f8e949b5a7f

111

py

Python

api/v1/generics/__init__.py

blockomat2100/vulnman

835ff3aae1168d8e2fa5556279bc86efd2e46472

[ "MIT" ]

null

api/v1/generics/__init__.py

blockomat2100/vulnman

835ff3aae1168d8e2fa5556279bc86efd2e46472

[ "MIT" ]

23

2021-12-01T10:00:38.000Z

2021-12-11T11:43:13.000Z

api/v1/generics/__init__.py

blockomat2100/vulnman

835ff3aae1168d8e2fa5556279bc86efd2e46472

[ "MIT" ]

null

from api.v1.generics.agents import AgentModelViewSet from api.v1.generics.session import ProjectSessionViewSet

37

57

0.873874

14

111

6.928571

0.642857

0.14433

0.185567

0.350515

0

0.019417

0.072072

111

2

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55.5

0.92233

0

1

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true

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1

0

null

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1

0

null

0

1

0

1

0

1

0

7

acf4de65fe52fc412eed03ac739a9e84a93edfa3

172

py

Python

autonomous_systems_project/agents/__init__.py

alessandropacielli/autonomous_systems_project

ae429099409356db5cdd19597af871f239300ffb

[ "MIT" ]

null

autonomous_systems_project/agents/__init__.py

alessandropacielli/autonomous_systems_project

ae429099409356db5cdd19597af871f239300ffb

[ "MIT" ]

null

autonomous_systems_project/agents/__init__.py

alessandropacielli/autonomous_systems_project

ae429099409356db5cdd19597af871f239300ffb

[ "MIT" ]

null

from autonomous_systems_project.agents.actor_critic import * from autonomous_systems_project.agents.double_dqn import * from autonomous_systems_project.agents.dqn import *

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0

8

4a080ae13c876589897cf230e6a792ce74c2dcb1

24,987

py

Python

NetworkControllability/TmpEdgeAttackExperiments.py

xinfeng1i/NetworkControllability

8a22ad0498ea12438c132556814dc255e709dc01

[ "BSD-2-Clause" ]

1

2019-02-06T13:39:49.000Z

NetworkControllability/TmpEdgeAttackExperiments.py

python27/NetworkControllability

8a22ad0498ea12438c132556814dc255e709dc01

[ "BSD-2-Clause" ]

1

2020-11-03T22:51:32.000Z

2020-11-06T11:48:28.000Z

NetworkControllability/TmpEdgeAttackExperiments.py

xinfeng1i/NetworkControllability

8a22ad0498ea12438c132556814dc255e709dc01

[ "BSD-2-Clause" ]

null

import networkx as nx import matplotlib.pyplot as plt import exact_controllability as ECT from networkx.utils import powerlaw_sequence import operator import random import csv import copy import subprocess, os import time import numpy as np from ControllabilityRobustnessBasedOnEdgeAttack import RandomEdgeAttack from ControllabilityRobustnessBasedOnEdgeAttack import InitialEdgeDegreeAttack from ControllabilityRobustnessBasedOnEdgeAttack import RecalculatedEdgeDegreeAttack from ControllabilityRobustnessBasedOnEdgeAttack import InitialEdgeBetweennessAttack from ControllabilityRobustnessBasedOnEdgeAttack import RecalculatedEdgeBetweennessAttack import strutral_controllability as SC def EdgeAttackBA(): start_time = time.time() n = 200 m = 3 fraction = 0.2 E = 591 E_rm = 118 run_cnt = 100 #******** Run Node Attack 1 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) rndseed = 0 for i in range(run_cnt): G1 = nx.barabasi_albert_graph(n, m, seed=rndseed) print ">>>>>>>>>>>>>>> Random Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = RandomEdgeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] rndseed += 1 tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack1_BA.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) #******** Run Node Attack 2 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) rndseed = 0 for i in range(run_cnt): G1 = nx.barabasi_albert_graph(n, m, seed=rndseed) print ">>>>>>>>>>>>>>> Initial Degree Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = InitialEdgeDegreeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] rndseed += 1 tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack2_BA.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) #******** Run Node Attack 3 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) rndseed = 0 for i in range(run_cnt): G1 = nx.barabasi_albert_graph(n, m, seed=rndseed) print ">>>>>>>>>>>>>>> Recalculated Degree Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = RecalculatedEdgeDegreeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] rndseed += 1 tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack3_BA.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) #******** Run Node Attack 4 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) rndseed = 0 for i in range(run_cnt): G1 = nx.barabasi_albert_graph(n, m, seed=rndseed) print ">>>>>>>>>>>>>>> Initial Betweenness Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = InitialEdgeBetweennessAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] rndseed += 1 tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack4_BA.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) #******** Run Node Attack 5 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) rndseed = 0 for i in range(run_cnt): G1 = nx.barabasi_albert_graph(n, m, seed=rndseed) print ">>>>>>>>>>>>>>> Recalculated Betweenness Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = RecalculatedEdgeBetweennessAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] rndseed += 1 tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack5_BA.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) print "--- cost time %s seconds ---" %(time.time() - start_time) def EdgeAttackUSAir(): start_time = time.time() n = 332 fraction = 0.2 E = 2126 E_rm = int(0.2 * E) run_cnt = 100 #******** Run Edge Attack 1 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) rndseed = 1; for i in range(run_cnt): G1 = nx.read_pajek("dataset/USAir97.net") print ">>>>>>>>>>>>>>> Random Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) random.seed(rndseed) ND1, T1 = RandomEdgeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] rndseed += 1; tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack1_USAir.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) run_cnt = 3 #******** Run Edge Attack 2 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) for i in range(run_cnt): G1 = nx.read_pajek("dataset/USAir97.net") print ">>>>>>>>>>>>>>> Initial Degree Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = InitialEdgeDegreeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack2_USAir.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) run_cnt = 3 #******** Run Edge Attack 3 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) for i in range(run_cnt): G1 = nx.read_pajek("dataset/USAir97.net") print ">>>>>>>>>>>>>>> Recalculated Degree Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = RecalculatedEdgeDegreeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack3_USAir.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) run_cnt = 3 #******** Run Edge Attack 4 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) for i in range(run_cnt): G1 = nx.read_pajek("dataset/USAir97.net") print ">>>>>>>>>>>>>>> Initial Betweenness Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = InitialEdgeBetweennessAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack4_USAir.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) run_cnt = 3 #******** Run Edge Attack 5 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) for i in range(run_cnt): G1 = nx.read_pajek("dataset/USAir97.net") print ">>>>>>>>>>>>>>> Recalculated Betweenness Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = RecalculatedEdgeBetweennessAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack5_USAir.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) print "--- cost time %s seconds ---" %(time.time() - start_time) def EdgeAttackErdosNetwork(): start_time = time.time() n = 429 fraction = 0.2 E = 1312 E_rm = int(0.2 * E) run_cnt = 30 #******** Run Node Attack 1 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) rndseed = 1 for i in range(run_cnt): G = nx.read_pajek("dataset/Erdos971_revised.net") G1 = max(nx.connected_component_subgraphs(G),key=len) print ">>>>>>>>>>>>>>> Random Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) random.seed(rndseed) ND1, T1 = RandomEdgeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] rndseed += 1 tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack1_ErdosNetwork.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) run_cnt = 1 random.seed() #******** Run Node Attack 2 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) for i in range(run_cnt): G = nx.read_pajek("dataset/Erdos971_revised.net") G1 = max(nx.connected_component_subgraphs(G),key=len) print ">>>>>>>>>>>>>>> Initial Degree Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = InitialEdgeDegreeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack2_ErdosNetwork.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) run_cnt = 1 random.seed() #******** Run Node Attack 3 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) for i in range(run_cnt): G = nx.read_pajek("dataset/Erdos971_revised.net") G1 = max(nx.connected_component_subgraphs(G),key=len) print ">>>>>>>>>>>>>>> Recalculated Degree Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = RecalculatedEdgeDegreeAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack3_ErdosNetwork.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) run_cnt = 1 random.seed() #******** Run Node Attack 4 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) for i in range(run_cnt): G = nx.read_pajek("dataset/Erdos971_revised.net") G1 = max(nx.connected_component_subgraphs(G),key=len) print ">>>>>>>>>>>>>>> Initial Betweenness Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = InitialEdgeBetweennessAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack4_ErdosNetwork.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) run_cnt = 1 random.seed() #******** Run Node Attack 5 ********# tot_ND1 = [0] * (E_rm + 1) tot_T1 = [0] * (E_rm + 1) for i in range(run_cnt): G = nx.read_pajek("dataset/Erdos971_revised.net") G1 = max(nx.connected_component_subgraphs(G),key=len) print ">>>>>>>>>>>>>>> Recalculated Betweenness Attack run time count: ", i + 1, "<<<<<<<<<<<<<<<<<<" print "graph info", nx.info(G1) ND1, T1 = RecalculatedEdgeBetweennessAttack(G1, remove_fraction=fraction) tot_ND1 = [x + y for x, y in zip(tot_ND1, ND1)] tot_ND1 = [((x + 0.0) / run_cnt) for x in tot_ND1] tot_T1 = T1 tot_ND1 = [(x + 0.0) / (n + 0.0) for x in tot_ND1] tot_T1 = [(x + 0.0) / (E + 0.0) for x in tot_T1] with open("results2/edge_attack5_ErdosNetwork.csv", "w") as f: writer = csv.writer(f, delimiter=',') writer.writerows(zip(tot_T1, tot_ND1)) print "--- cost time %s seconds ---" %(time.time() - start_time) def ReadPajek(filename): '''Read pajek file to construct DiGraph''' G = nx.DiGraph() fp = open(filename, 'r') line = fp.readline() while line: if line[0] == '*': line = line.strip().split() label = line[0] number = int(line[1]) if label == '*Vertices' or label == '*vertices': NodeNum = number for i in range(NodeNum): NodeLine = fp.readline() NodeLine = NodeLine.strip().split() NodeID = int(NodeLine[0]) NodeLabel = NodeLine[1] G.add_node(NodeID) elif label == '*Arcs' or label == '*arcs': EdgeNum = number for i in range(EdgeNum): EdgeLine = fp.readline() EdgeLine = EdgeLine.strip().split() u = int(EdgeLine[0]) v = int(EdgeLine[1]) #w = float(EdgeLine[2]) G.add_edge(u, v) else: pass line = fp.readline() fp.close() return G def EdgeAttack(G): """ Edge attack experiments on real world networks Params: G: A directed network of networkx Returns: None. Print the network controllability n_D after 5% 10% 15% 20% edges removed """ NodesNum = G.number_of_nodes() EdgesNum = G.number_of_edges() # Edge remove fraction F0, F1, F2, F3, F4 F1 = 0.05 F2 = 0.10 F3 = 0.15 F4 = 0.20 LRA = [] LID = [] LRD = [] LIB = [] LRB = [] # Following is Edge Random Attack (RA) print '########## Edge RA ##########' G1 = copy.deepcopy(G) RandomEdges = copy.deepcopy(G1.edges()) random.shuffle(RandomEdges) i = 0 while i < int(F1 * EdgesNum): u, v = RandomEdges[i] G1.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G1)) / (NodesNum + 0.0) print F1, nD LRA.append(nD) while i < int(F2 * EdgesNum): u, v = RandomEdges[i] G1.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G1)) / (NodesNum + 0.0) print F2, nD LRA.append(nD) while i < int(F3 * EdgesNum): u, v = RandomEdges[i] G1.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G1)) / (NodesNum + 0.0) print F3, nD LRA.append(nD) while i < int(F4 * EdgesNum): u, v = RandomEdges[i] G1.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G1)) / (NodesNum + 0.0) print F4, nD LRA.append(nD) G1.clear() RandomEdges = [] # Following is Initial Edge Degree Attack (IDA) print '########## Edge IDA ##########' G2 = copy.deepcopy(G) NodeDegrees = nx.degree(G2) EdgeDegrees = {} for u, v in G2.edges_iter(): # Calculate the edge degrees EdgeDegrees[(u, v)] = NodeDegrees[u] * NodeDegrees[v] # Sort the edges decrendingly according to edge degree SortedEdges = sorted(EdgeDegrees, key=EdgeDegrees.get, reverse=True) i = 0 while i < int(F1 * EdgesNum): u, v = SortedEdges[i] G2.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G2)) / (NodesNum + 0.0) print F1, nD LID.append(nD) while i < int(F2 * EdgesNum): u, v = SortedEdges[i] G2.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G2)) / (NodesNum + 0.0) print F2, nD LID.append(nD) while i < int(F3 * EdgesNum): u, v = SortedEdges[i] G2.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G2)) / (NodesNum + 0.0) print F3, nD LID.append(nD) while i < int(F4 * EdgesNum): u, v = SortedEdges[i] G2.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G2)) / (NodesNum + 0.0) print F4, nD LID.append(nD) G2.clear() NodeDegrees = {} EdgeDegrees = {} SortedEdges = [] # Following is Recalculated Edge Degree Attack (RDA) print '########## Edge RDA ##########' G3 = copy.deepcopy(G) i = 0 while i < int(F1 * EdgesNum): # Find the edge with max edge degree at present MaxU = -1; MaxV = -1; MaxDegree = -1; NodeDegrees = nx.degree(G3) for (u, v) in G3.edges_iter(): CurDegree = NodeDegrees[u] * NodeDegrees[v] if CurDegree > MaxDegree: MaxDegree = CurDegree MaxU = u MaxV = v G3.remove_edge(MaxU, MaxV) i += 1 nD = len(SC.control_nodes(G3)) / (NodesNum + 0.0) print F1, nD LRD.append(nD) while i < int(F2 * EdgesNum): # Find the edge with max edge degree at present MaxU = -1; MaxV = -1; MaxDegree = -1; NodeDegrees = nx.degree(G3) for (u, v) in G3.edges_iter(): CurDegree = NodeDegrees[u] * NodeDegrees[v] if CurDegree > MaxDegree: MaxDegree = CurDegree MaxU = u MaxV = v G3.remove_edge(MaxU, MaxV) i += 1 nD = len(SC.control_nodes(G3)) / (NodesNum + 0.0) print F2, nD LRD.append(nD) while i < int(F3 * EdgesNum): # Find the edge with max edge degree at present MaxU = -1; MaxV = -1; MaxDegree = -1; NodeDegrees = nx.degree(G3) for (u, v) in G3.edges_iter(): CurDegree = NodeDegrees[u] * NodeDegrees[v] if CurDegree > MaxDegree: MaxDegree = CurDegree MaxU = u MaxV = v G3.remove_edge(MaxU, MaxV) i += 1 nD = len(SC.control_nodes(G3)) / (NodesNum + 0.0) print F3, nD LRD.append(nD) while i < int(F4 * EdgesNum): # Find the edge with max edge degree at present MaxU = -1; MaxV = -1; MaxDegree = -1; NodeDegrees = nx.degree(G3) for (u, v) in G3.edges_iter(): CurDegree = NodeDegrees[u] * NodeDegrees[v] if CurDegree > MaxDegree: MaxDegree = CurDegree MaxU = u MaxV = v G3.remove_edge(MaxU, MaxV) i += 1 nD = len(SC.control_nodes(G3)) / (NodesNum + 0.0) print F4, nD LRD.append(nD) G3.clear() # Folloing is Initial Edge Betweenness Attack (IBA) print '########## Edge IBA ##########' G4 = copy.deepcopy(G) EdgeBetweenness = nx.edge_betweenness_centrality(G4) SortedBetEdges = sorted(EdgeBetweenness, key=EdgeBetweenness.get, reverse=True) i = 0 while i < int(F1 * EdgesNum): u, v = SortedBetEdges[i] G4.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G4)) / (NodesNum + 0.0) print F1, nD LIB.append(nD) while i < int(F2 * EdgesNum): u, v = SortedBetEdges[i] G4.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G4)) / (NodesNum + 0.0) print F2, nD LIB.append(nD) while i < int(F3 * EdgesNum): u, v = SortedBetEdges[i] G4.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G4)) / (NodesNum + 0.0) print F3, nD LIB.append(nD) while i < int(F4 * EdgesNum): u, v = SortedBetEdges[i] G4.remove_edge(u, v) i += 1 nD = len(SC.control_nodes(G4)) / (NodesNum + 0.0) print F4, nD LIB.append(nD) G4.clear() EdgeBetweenness = {} SortedBetEdges = [] # Following is Recalculated Edge Betweenness Attack (RBA) print '########## Edge RBA ##########' G5 = copy.deepcopy(G) i = 0 while i < int(F1 * EdgesNum): EdgeBets = nx.edge_betweenness_centrality(G5) # Find the edge with Max edge betweenness uMax = -1; vMax = -1; betMax = -1.0; for ((u, v), bet) in EdgeBets.iteritems(): if bet > betMax: betMax = bet uMax = u vMax = v G5.remove_edge(uMax, vMax) i += 1 nD = len(SC.control_nodes(G5)) / (NodesNum + 0.0) print F1, nD LRB.append(nD) while i < int(F2 * EdgesNum): EdgeBets = nx.edge_betweenness_centrality(G5) # Find the edge with Max edge betweenness uMax = -1; vMax = -1; betMax = -1.0; for ((u, v), bet) in EdgeBets.iteritems(): if bet > betMax: betMax = bet uMax = u vMax = v G5.remove_edge(uMax, vMax) i += 1 nD = len(SC.control_nodes(G5)) / (NodesNum + 0.0) print F2, nD LRB.append(nD) while i < int(F3 * EdgesNum): EdgeBets = nx.edge_betweenness_centrality(G5) # Find the edge with Max edge betweenness uMax = -1; vMax = -1; betMax = -1.0; for ((u, v), bet) in EdgeBets.iteritems(): if bet > betMax: betMax = bet uMax = u vMax = v G5.remove_edge(uMax, vMax) i += 1 nD = len(SC.control_nodes(G5)) / (NodesNum + 0.0) print F3, nD LRB.append(nD) while i < int(F4 * EdgesNum): EdgeBets = nx.edge_betweenness_centrality(G5) # Find the edge with Max edge betweenness uMax = -1; vMax = -1; betMax = -1.0; for ((u, v), bet) in EdgeBets.iteritems(): if bet > betMax: betMax = bet uMax = u vMax = v G5.remove_edge(uMax, vMax) i += 1 nD = len(SC.control_nodes(G5)) / (NodesNum + 0.0) print F4, nD LRB.append(nD) G5.clear() print 'RA: ', LRA[0], LRA[1], LRA[2], LRA[3] print 'ID: ', LID[0], LID[1], LID[2], LID[3] print 'RD: ', LRD[0], LRD[1], LRD[2], LRD[3] print 'IB: ', LIB[0], LIB[1], LIB[2], LIB[3] print 'RB: ', LRB[0], LRB[1], LRB[2], LRB[3] if __name__ == "__main__": #EdgeAttackBA() #EdgeAttackUSAir() # Edge Attack Erdos971 Network # for random attack, we set the random seed to from 1 to 100 for the # independent 100 runs. For other deliberate attacks, as the attack order # is fixed, we reset the seed of random to the initial state, i.e. seed(None) #EdgeAttackErdosNetwork() # Regulatory #G = ReadPajek('./dataset/Regulatory/TRN-Yeast-1.net') #G = ReadPajek('./dataset/Regulatory/TRN-Yeast-2.net') #G = ReadPajek('./dataset/Regulatory/TRN-EC-2.net') #G = ReadPajek('./dataset/Regulatory/Ownership.net') # World Wide Web (WWW) G = ReadPajek('./dataset/WWW/PoliticalBlogs.net') print 'Edge Attack From Temp Files ... ' print 'WWW --- PoliticalBlogs' NodesNum = G.number_of_nodes() EdgesNum = G.number_of_edges() DriverNodes = SC.control_nodes(G) nD = len(DriverNodes) / (NodesNum + 0.0) print 'Nodes Num: ', NodesNum print 'Edges Num: ', EdgesNum print 'nD = ', nD EdgeAttack(G)

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null

0

1

0

7

4a13bacba15ebf17c8cfc42cad96cd3b58f57140

305

py

Python

crypt.py

heyrict/formify

eebd7bb3685a892adb0e4ac82ad34b6610bd0a4e

[ "Apache-2.0" ]

1

2021-06-19T19:32:01.000Z

crypt.py

heyrict/formify

eebd7bb3685a892adb0e4ac82ad34b6610bd0a4e

[ "Apache-2.0" ]

null

crypt.py

heyrict/formify

eebd7bb3685a892adb0e4ac82ad34b6610bd0a4e

[ "Apache-2.0" ]

null

import bcrypt class Bcrypt(object): def get_hashed_password(plain_text_password): return bcrypt.hashpw(plain_text_password.encode(), bcrypt.gensalt()) def check_password(plain_text_password, hashed_password): return bcrypt.checkpw(plain_text_password.encode(), hashed_password)

30.5

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7

680f5487f3c7b14f1073a9e3723d4f09b3722c0f

77

py

Python

trot_analysis/__init__.py

chrishavlin/trot_analysis

e1adb2af3faba6e1875a96ef1f9a71b11aa941f6

[ "MIT" ]

1

2020-11-30T02:38:33.000Z

trot_analysis/__init__.py

chrishavlin/trot_analysis

e1adb2af3faba6e1875a96ef1f9a71b11aa941f6

[ "MIT" ]

null

trot_analysis/__init__.py

chrishavlin/trot_analysis

e1adb2af3faba6e1875a96ef1f9a71b11aa941f6

[ "MIT" ]

null

from trot_analysis.trotters import trotters from trot_analysis import awards

25.666667

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28,836

py

Python

python_msx_sdk/api/services_api.py

CiscoDevNet/python-msx-sdk

d7e0a08c656504b4f4551d263e67c671a2a04b3f

[ "MIT" ]

null

python_msx_sdk/api/services_api.py

CiscoDevNet/python-msx-sdk

d7e0a08c656504b4f4551d263e67c671a2a04b3f

[ "MIT" ]

null

python_msx_sdk/api/services_api.py

CiscoDevNet/python-msx-sdk

d7e0a08c656504b4f4551d263e67c671a2a04b3f

[ "MIT" ]

null

""" MSX SDK MSX SDK client. # noqa: E501 The version of the OpenAPI document: 1.0.9 Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from python_msx_sdk.api_client import ApiClient, Endpoint as _Endpoint from python_msx_sdk.model_utils import ( # noqa: F401 check_allowed_values, check_validations, date, datetime, file_type, none_type, validate_and_convert_types ) from python_msx_sdk.model.error import Error from python_msx_sdk.model.legacy_service_order import LegacyServiceOrder from python_msx_sdk.model.legacy_service_order_response import LegacyServiceOrderResponse from python_msx_sdk.model.service import Service from python_msx_sdk.model.service_update import ServiceUpdate from python_msx_sdk.model.services_page import ServicesPage class ServicesApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def __delete_service( self, id, **kwargs ): """Deletes a service. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_service(id, async_req=True) >>> result = thread.get() Args: id (str): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: None If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.call_with_http_info(**kwargs) self.delete_service = _Endpoint( settings={ 'response_type': None, 'auth': [], 'endpoint_path': '/manage/api/v8/services/{id}', 'operation_id': 'delete_service', 'http_method': 'DELETE', 'servers': None, }, params_map={ 'all': [ 'id', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client, callable=__delete_service ) def __get_service( self, id, **kwargs ): """Returns a service. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_service(id, async_req=True) >>> result = thread.get() Args: id (str): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: Service If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.call_with_http_info(**kwargs) self.get_service = _Endpoint( settings={ 'response_type': (Service,), 'auth': [], 'endpoint_path': '/manage/api/v8/services/{id}', 'operation_id': 'get_service', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'id', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client, callable=__get_service ) def __get_services_page( self, page, page_size, **kwargs ): """Returns a page of services. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_services_page(page, page_size, async_req=True) >>> result = thread.get() Args: page (int): page_size (int): Keyword Args: tenant_ids ([str]): [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ServicesPage If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['page'] = \ page kwargs['page_size'] = \ page_size return self.call_with_http_info(**kwargs) self.get_services_page = _Endpoint( settings={ 'response_type': (ServicesPage,), 'auth': [], 'endpoint_path': '/manage/api/v8/services', 'operation_id': 'get_services_page', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'page', 'page_size', 'tenant_ids', ], 'required': [ 'page', 'page_size', ], 'nullable': [ ], 'enum': [ ], 'validation': [ 'page', 'page_size', ] }, root_map={ 'validations': { ('page',): { 'inclusive_minimum': 0, }, ('page_size',): { 'inclusive_maximum': 1000, 'inclusive_minimum': 1, }, }, 'allowed_values': { }, 'openapi_types': { 'page': (int,), 'page_size': (int,), 'tenant_ids': ([str],), }, 'attribute_map': { 'page': 'page', 'page_size': 'pageSize', 'tenant_ids': 'tenantIds', }, 'location_map': { 'page': 'query', 'page_size': 'query', 'tenant_ids': 'query', }, 'collection_format_map': { 'tenant_ids': 'multi', } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client, callable=__get_services_page ) def __submit_order( self, product_id, offer_id, legacy_service_order, **kwargs ): """Submits an order. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.submit_order(product_id, offer_id, legacy_service_order, async_req=True) >>> result = thread.get() Args: product_id (str): offer_id (str): legacy_service_order (LegacyServiceOrder): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: LegacyServiceOrderResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['product_id'] = \ product_id kwargs['offer_id'] = \ offer_id kwargs['legacy_service_order'] = \ legacy_service_order return self.call_with_http_info(**kwargs) self.submit_order = _Endpoint( settings={ 'response_type': (LegacyServiceOrderResponse,), 'auth': [], 'endpoint_path': '/manage/api/v8/services', 'operation_id': 'submit_order', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'product_id', 'offer_id', 'legacy_service_order', ], 'required': [ 'product_id', 'offer_id', 'legacy_service_order', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'product_id': (str,), 'offer_id': (str,), 'legacy_service_order': (LegacyServiceOrder,), }, 'attribute_map': { 'product_id': 'productId', 'offer_id': 'offerId', }, 'location_map': { 'product_id': 'query', 'offer_id': 'query', 'legacy_service_order': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client, callable=__submit_order ) def __update_order( self, product_id, offer_id, legacy_service_order, **kwargs ): """Updates an order. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_order(product_id, offer_id, legacy_service_order, async_req=True) >>> result = thread.get() Args: product_id (str): offer_id (str): legacy_service_order (LegacyServiceOrder): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: LegacyServiceOrderResponse If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['product_id'] = \ product_id kwargs['offer_id'] = \ offer_id kwargs['legacy_service_order'] = \ legacy_service_order return self.call_with_http_info(**kwargs) self.update_order = _Endpoint( settings={ 'response_type': (LegacyServiceOrderResponse,), 'auth': [], 'endpoint_path': '/manage/api/v8/services', 'operation_id': 'update_order', 'http_method': 'PUT', 'servers': None, }, params_map={ 'all': [ 'product_id', 'offer_id', 'legacy_service_order', ], 'required': [ 'product_id', 'offer_id', 'legacy_service_order', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'product_id': (str,), 'offer_id': (str,), 'legacy_service_order': (LegacyServiceOrder,), }, 'attribute_map': { 'product_id': 'productId', 'offer_id': 'offerId', }, 'location_map': { 'product_id': 'query', 'offer_id': 'query', 'legacy_service_order': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client, callable=__update_order ) def __update_service( self, id, service_update, **kwargs ): """Updates a service. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_service(id, service_update, async_req=True) >>> result = thread.get() Args: id (str): service_update (ServiceUpdate): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: Service If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id kwargs['service_update'] = \ service_update return self.call_with_http_info(**kwargs) self.update_service = _Endpoint( settings={ 'response_type': (Service,), 'auth': [], 'endpoint_path': '/manage/api/v8/services/{id}', 'operation_id': 'update_service', 'http_method': 'PUT', 'servers': None, }, params_map={ 'all': [ 'id', 'service_update', ], 'required': [ 'id', 'service_update', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (str,), 'service_update': (ServiceUpdate,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', 'service_update': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client, callable=__update_service )

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101

0.446595

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28,836

5.07131

0.082919

0.030903

0.025507

0.026488

0.867479

0.852273

0.847531

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0.82791

0.813849

0

0.003336

0.469829

28,836

819

102

35.208791

0.796769

0.305798

0

0.653501

1

0

0.211497

0.030814

0

1

0.012567

false

0

0.017953

0

0.043088

0

null

0

1

0

1

0

null

0

7

a85874908f4ac7d17c5abdbf8b971fe06fab0c18

92

py

Python

augur/metrics/repo_meta/__init__.py

Claire-Hough/augur

b48d246a8959f62473c8e898148a2113772a700c

[ "MIT" ]

3

2019-10-31T19:07:48.000Z

2019-11-20T23:14:15.000Z

augur/metrics/repo_meta/__init__.py

Claire-Hough/augur

b48d246a8959f62473c8e898148a2113772a700c

[ "MIT" ]

3

2019-12-03T21:21:17.000Z

2019-12-05T15:26:22.000Z

augur/metrics/repo_meta/__init__.py

Claire-Hough/augur

b48d246a8959f62473c8e898148a2113772a700c

[ "MIT" ]

4

2019-11-05T20:22:12.000Z

2019-12-12T18:08:30.000Z

from .repo_meta import create_repo_meta_metrics from .routes import create_repo_meta_routes

30.666667

47

0.891304

15

92

5

0.466667

0.32

0.426667

0.533333

0

0.086957

92

3

48

30.666667

0.892857

0

1

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true

0

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1

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1

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null

0

1

0

1

0

1

0

8

a87dfa582c7ab24d706467107ffdc96d9bcc6b9e

23,058

py

Python

WAnet/training.py

THREDgroup/WAnet

2b160012880f05f8ea3abcc426fb53eedfd51f80

[ "MIT" ]

null

WAnet/training.py

THREDgroup/WAnet

2b160012880f05f8ea3abcc426fb53eedfd51f80

[ "MIT" ]

null

WAnet/training.py

THREDgroup/WAnet

2b160012880f05f8ea3abcc426fb53eedfd51f80

[ "MIT" ]

null

import keras import sklearn.model_selection import numpy import pkg_resources import os VERBOSE = 1 def load_data(): curves = numpy.load(pkg_resources.resource_filename('WAnet', 'data/compiled_data/data_curves.npz'))['curves'] geometry = numpy.load(pkg_resources.resource_filename('WAnet', 'data/compiled_data/data_geometry.npz'))['geometry'] constants = numpy.load(pkg_resources.resource_filename('WAnet', 'data/compiled_data/constants.npz')) S = constants['S'] N = constants['N'] D = constants['D'] F = constants['F'] G = constants['G'] new_curves = numpy.zeros((S*N, D * F)) for i, curveset in enumerate(curves): new_curves[i, :] = curveset.T.flatten() / 1000000 new_geometry = numpy.zeros((S*N, G * G * G)) for i, geometryset in enumerate(geometry): new_geometry[i, :] = geometryset.T.flatten() return curves, geometry, S, N, D, F, G, new_curves, new_geometry def train_geometry_autoencoder(epochs, latent_dim, save_results, print_network): curves, geometry, S, N, D, F, G, new_curves, new_geometry = load_data() batch_size = 100 original_dim = G*G*G intermediate_dim = 256 epsilon_std = 1.0 x = keras.layers.Input(shape=(original_dim,)) h = keras.layers.Dense(intermediate_dim, activation='relu')(x) z_mean = keras.layers.Dense(latent_dim)(h) z_log_var = keras.layers.Dense(latent_dim)(h) def sampling(args): z_mean, z_log_var = args epsilon = keras.backend.random_normal(shape=(keras.backend.shape(z_mean)[0], latent_dim), mean=0., stddev=epsilon_std) return z_mean + keras.backend.exp(z_log_var / 2) * epsilon # note that "output_shape" isn't necessary with the TensorFlow backend z = keras.layers.Lambda(sampling, output_shape=(latent_dim,))([z_mean, z_log_var]) # we instantiate these layers separately so as to reuse them later decoder_h = keras.layers.Dense(intermediate_dim, activation='relu') decoder_mean = keras.layers.Dense(original_dim, activation='sigmoid') h_decoded = decoder_h(z) x_decoded_mean = decoder_mean(h_decoded) # Custom loss layer class CustomVariationalLayer(keras.layers.Layer): def __init__(self, **kwargs): self.is_placeholder = True super(CustomVariationalLayer, self).__init__(**kwargs) def vae_loss(self, x, x_decoded_mean): xent_loss = original_dim * keras.metrics.binary_crossentropy(x, x_decoded_mean) kl_loss = - 0.5 * keras.backend.sum(1 + z_log_var - keras.backend.square(z_mean) - keras.backend.exp(z_log_var), axis=-1) return keras.backend.mean(xent_loss + kl_loss) def call(self, inputs, **kwargs): x = inputs[0] x_decoded_mean = inputs[1] loss = self.vae_loss(x, x_decoded_mean) self.add_loss(loss, inputs=inputs) # We won't actually use the output. return x y = CustomVariationalLayer()([x, x_decoded_mean]) vae = keras.models.Model(x, y) vae.compile(optimizer='rmsprop', loss=None) x_train, x_test = sklearn.model_selection.train_test_split(new_geometry, shuffle=False) weights = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'temp_vae_weights.h5') logger = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_vae_training.csv') vae.fit(x_train, shuffle=True, epochs=epochs, batch_size=batch_size, validation_data=(x_test, None), verbose=VERBOSE, callbacks=[keras.callbacks.ModelCheckpoint(filepath=weights, verbose=VERBOSE, save_best_only=True), keras.callbacks.CSVLogger(logger, separator=',', append=False)]) vae.load_weights(weights) os.remove(weights) # build a model to project inputs on the latent space encoder = keras.models.Model(x, z_mean) # build a digit generator that can sample from the learned distribution decoder_input = keras.layers.Input(shape=(latent_dim,)) _h_decoded = decoder_h(decoder_input) _x_decoded_mean = decoder_mean(_h_decoded) generator = keras.models.Model(decoder_input, _x_decoded_mean) # Build and save the autoencoder _h_decoded2 = decoder_h(z_mean) _x_decoded_mean2 = decoder_mean(_h_decoded2) autoencoder = keras.models.Model(x, _x_decoded_mean2) structure = [] weights = [] if save_results: # Save encoder structure and weights temp = open(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_encoder_structure.yml'), 'w') temp.write(encoder.to_yaml()) temp.close() encoder.save_weights(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_encoder_weights.h5')) # Save decoder structure and weights temp = open(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_decoder_structure.yml'), 'w') temp.write(generator.to_yaml()) temp.close() generator.save_weights(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_decoder_weights.h5')) # Save full autoencoder structure and weights structure = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_autoencoder_structure.yml') weights = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_autoencoder_weights.h5') temp = open(structure, 'w') temp.write(autoencoder.to_yaml()) temp.close() autoencoder.save_weights(weights) if print_network: keras.utils.plot_model(generator, to_file=pkg_resources.resource_filename('WAnet', 'figures/'+str(latent_dim)+'geometry_decoder.eps'), show_shapes=True) keras.utils.plot_model(encoder, to_file=pkg_resources.resource_filename('WAnet', 'figures/'+str(latent_dim)+'geometry_encoder.eps'), show_shapes=True) keras.utils.plot_model(autoencoder, to_file=pkg_resources.resource_filename('WAnet', 'figures/'+str(latent_dim)+'geometry_autoencoder.eps'), show_shapes=True) # Final check on metrics x_pred = autoencoder.predict(x_test) mse = keras.backend.mean(keras.losses.binary_crossentropy(x_pred, x_test)).eval() x_pred.fill(numpy.mean(x_test.flatten())) s2 = keras.backend.mean(keras.losses.binary_crossentropy(x_pred, x_test)).eval() r2 = 1-mse/s2 print("Final BCE: "+str(mse)) print("Final S2: "+str(s2)) print("Final R2: "+str(r2)) return r2 def train_response_autoencoder(epochs, latent_dim, save_results, print_network): curves, geometry, S, N, D, F, G, new_curves, new_geometry = load_data() batch_size = 10 original_dim = D*F intermediate_dim = 64 epsilon_std = 1.0 x = keras.layers.Input(shape=(original_dim,)) h = keras.layers.Dense(intermediate_dim, activation='relu')(x) z_mean = keras.layers.Dense(latent_dim)(h) z_log_var = keras.layers.Dense(latent_dim)(h) def sampling(args): z_mean, z_log_var = args epsilon = keras.backend.random_normal(shape=(keras.backend.shape(z_mean)[0], latent_dim), mean=0., stddev=epsilon_std) return z_mean + keras.backend.exp(z_log_var / 2) * epsilon # note that "output_shape" isn't necessary with the TensorFlow backend z = keras.layers.Lambda(sampling, output_shape=(latent_dim,))([z_mean, z_log_var]) # we instantiate these layers separately so as to reuse them later decoder_h = keras.layers.Dense(intermediate_dim, activation='relu') decoder_mean = keras.layers.Dense(original_dim, activation='sigmoid') h_decoded = decoder_h(z) x_decoded_mean = decoder_mean(h_decoded) # Custom loss layer class CustomVariationalLayer(keras.layers.Layer): def __init__(self, **kwargs): self.is_placeholder = True super(CustomVariationalLayer, self).__init__(**kwargs) def vae_loss(self, x, x_decoded_mean): xent_loss = original_dim * keras.metrics.mean_squared_error(x, x_decoded_mean) kl_loss = - 0.5 * keras.backend.sum(1 + z_log_var - keras.backend.square(z_mean) - keras.backend.exp(z_log_var), axis=-1) return keras.backend.mean(xent_loss + kl_loss) def call(self, inputs): x = inputs[0] x_decoded_mean = inputs[1] loss = self.vae_loss(x, x_decoded_mean) self.add_loss(loss, inputs=inputs) # We won't actually use the output. return x y = CustomVariationalLayer()([x, x_decoded_mean]) vae = keras.models.Model(x, y) vae.compile(optimizer='rmsprop', loss=None) # train the VAE on MNIST digits x_train, x_test = sklearn.model_selection.train_test_split(new_curves, shuffle=False) weights = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'temp_vae_weights.h5') logger = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_vae_training.csv') vae.fit(x_train, shuffle=True, epochs=epochs, batch_size=batch_size, validation_data=(x_test, None), verbose=VERBOSE, callbacks=[keras.callbacks.ModelCheckpoint(filepath=weights, verbose=VERBOSE, save_best_only=True), keras.callbacks.CSVLogger(logger, separator=',', append=False)]) vae.load_weights(weights) os.remove(weights) # build a model to project inputs on the latent space encoder = keras.models.Model(x, z_mean) # build a digit generator that can sample from the learned distribution decoder_input = keras.layers.Input(shape=(latent_dim,)) _h_decoded = decoder_h(decoder_input) _x_decoded_mean = decoder_mean(_h_decoded) generator = keras.models.Model(decoder_input, _x_decoded_mean) # Build and save the autoencoder _h_decoded2 = decoder_h(z_mean) _x_decoded_mean2 = decoder_mean(_h_decoded2) autoencoder = keras.models.Model(x, _x_decoded_mean2) if save_results: # Save encoder structure and weights temp = open(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_encoder_structure.yml'), 'w') temp.write(encoder.to_yaml()) temp.close() encoder.save_weights(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_encoder_weights.h5')) # Save decoder structure and weights temp = open(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_decoder_structure.yml'), 'w') temp.write(generator.to_yaml()) temp.close() generator.save_weights(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_decoder_weights.h5')) # Save full autoencoder structure and weights structure = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_autoencoder_structure.yml') weights = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_autoencoder_weights.h5') temp = open(structure, 'w') temp.write(autoencoder.to_yaml()) temp.close() autoencoder.save_weights(weights) if print_network: keras.utils.plot_model(generator, to_file=pkg_resources.resource_filename('WAnet', 'figures/'+str(latent_dim)+'curve_decoder.eps'), show_shapes=True) keras.utils.plot_model(encoder, to_file=pkg_resources.resource_filename('WAnet', 'figures/'+str(latent_dim)+'curve_encoder.eps'), show_shapes=True) keras.utils.plot_model(autoencoder, to_file=pkg_resources.resource_filename('WAnet', 'figures/'+str(latent_dim)+'curve_autoencoder.eps'), show_shapes=True) x_pred = autoencoder.predict(x_test) s2 = numpy.mean(numpy.power(numpy.mean(x_test.flatten()) - x_test.flatten(), 2)) mse = keras.backend.mean(keras.losses.mean_squared_error(x_pred, x_test)).eval() r2 = 1-mse/s2 print("Final MSE: "+str(mse)) print("Final S2: "+str(s2)) print("Final R2: "+str(r2)) return r2 def train_forward_network(epochs, latent_dim, save_results, print_network): curves, geometry, S, N, D, F, G, new_curves, new_geometry = load_data() # Define model x = keras.layers.Input(shape=(32768,)) de1 = keras.layers.Dense(256, activation='relu')(x) de2 = keras.layers.Dense(latent_dim, activation='relu')(de1) con = keras.layers.Dense(latent_dim, activation='relu')(de2) dd2 = keras.layers.Dense(64, activation='relu')(con) y = keras.layers.Dense(192, activation='sigmoid')(dd2) # Build and compile ,model mdl = keras.models.Model(x, y) mdl.compile(optimizer='rmsprop', loss='mse') # # Instantiate and freeze layers if possible temp = open(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_encoder_structure.yml'), 'r') geo = keras.models.model_from_yaml(temp.read()) geo.load_weights(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_encoder_weights.h5')) # Load curve autoencoder temp = open(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_decoder_structure.yml'), 'r') curve = keras.models.model_from_yaml(temp.read()) curve.load_weights(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_decoder_weights.h5')) mdl.layers[1].set_weights(geo.layers[1].get_weights()) mdl.layers[1].trainable = False mdl.layers[2].set_weights(geo.layers[2].get_weights()) mdl.layers[2].trainable = False mdl.layers[4].set_weights(curve.layers[1].get_weights()) mdl.layers[4].trainable = False mdl.layers[5].set_weights(curve.layers[2].get_weights()) mdl.layers[5].trainable = False # Make file names weights = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'forward_weights.h5') structure = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'forward_structure.yml') plot = pkg_resources.resource_filename('WAnet', 'figures/'+str(latent_dim)+'forward.eps') # Save model structure and start training x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(new_geometry, new_curves, shuffle=False) if save_results: mdl.fit(x_train, y_train, verbose=VERBOSE, epochs=epochs, shuffle=False, validation_data=(x_test, y_test), callbacks=[keras.callbacks.ModelCheckpoint(filepath=weights, verbose=VERBOSE, save_best_only=True)]) # Save decoder structure and weights temp = open(structure, 'w') temp.write(mdl.to_yaml()) temp.close() else: mdl.fit(new_geometry, new_curves, verbose=VERBOSE, epochs=epochs, shuffle=False, validation_data=(x_test, y_test)) if print_network: keras.utils.plot_model(mdl, to_file=plot, show_shapes=True) # mdl.load_weights(weights) y_pred = mdl.predict(x_test) s2 = numpy.mean(numpy.power(numpy.mean(y_test.flatten()) - y_test.flatten(), 2)) mse = keras.backend.mean(keras.losses.mean_squared_error(y_pred, y_test)).eval() r2 = 1-mse/s2 print("Final MSE: "+str(mse)) print("Final S2: "+str(s2)) print("Final R2: "+str(r2)) return r2 def train_inverse_network(epochs, latent_dim, save_results, print_network): curves, geometry, S, N, D, F, G, new_curves, new_geometry = load_data() # Define model x = keras.layers.Input(shape=(192,)) de1 = keras.layers.Dense(64, activation='relu')(x) de2 = keras.layers.Dense(latent_dim, activation='relu')(de1) con = keras.layers.Dense(latent_dim, activation='relu')(de2) dd2 = keras.layers.Dense(256, activation='relu')(con) y = keras.layers.Dense(32768, activation='sigmoid')(dd2) # Build and compile ,model mdl = keras.models.Model(x, y) mdl.compile(optimizer='rmsprop', loss='binary_crossentropy') # # Instantiate and freeze layers if possible temp = open(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_decoder_structure.yml'), 'r') geo = keras.models.model_from_yaml(temp.read()) geo.load_weights(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'geometry_decoder_weights.h5')) # Load curve autoencoder temp = open(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_encoder_structure.yml'), 'r') curve = keras.models.model_from_yaml(temp.read()) curve.load_weights(pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'curve_encoder_weights.h5')) mdl.layers[1].set_weights(curve.layers[1].get_weights()) mdl.layers[1].trainable = False mdl.layers[2].set_weights(curve.layers[2].get_weights()) mdl.layers[2].trainable = False mdl.layers[4].set_weights(geo.layers[1].get_weights()) mdl.layers[4].trainable = False mdl.layers[5].set_weights(geo.layers[2].get_weights()) mdl.layers[5].trainable = False # Make file names weights = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'inverse_weights.h5') structure = pkg_resources.resource_filename('WAnet', 'trained_models/'+str(latent_dim)+'inverse_structure.yml') plot = pkg_resources.resource_filename('WAnet', 'figures/'+str(latent_dim)+'inverse.eps') # Save model structure and start training x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(new_curves, new_geometry, shuffle=False) if save_results: mdl.fit(new_curves, new_geometry, verbose=VERBOSE, epochs=epochs, shuffle=False, validation_data=(x_test, y_test), callbacks=[keras.callbacks.ModelCheckpoint(filepath=weights, verbose=VERBOSE, save_best_only=True)]) # Save decoder structure and weights temp = open(structure, 'w') temp.write(mdl.to_yaml()) temp.close() else: mdl.fit(new_curves, new_geometry, verbose=VERBOSE, epochs=epochs, shuffle=False, validation_data=(x_test, y_test)) if print_network: keras.utils.plot_model(mdl, to_file=plot, show_shapes=True) # Final check on metrics mdl.load_weights(weights) y_pred = mdl.predict(x_test) mse = keras.backend.mean(keras.losses.binary_crossentropy(y_pred, y_test)).eval() y_pred.fill(numpy.mean(x_test.flatten())) s2 = keras.backend.mean(keras.losses.binary_crossentropy(y_pred, y_test)).eval() r2 = 1-mse/s2 print("Final BCE: "+str(mse)) print("Final S2: "+str(s2)) print("Final R2: "+str(r2)) return r2 def train_simple_inverse_network(epochs, save_results, print_network): curves, geometry, S, N, D, F, G, new_curves, new_geometry = load_data() # Define model x = keras.layers.Input(shape=(192,)) de1 = keras.layers.Dense(384, activation='relu')(x) de2 = keras.layers.Dense(768, activation='relu')(de1) con = keras.layers.Dense(1536, activation='relu')(de2) dd2 = keras.layers.Dense(3072, activation='relu')(con) y = keras.layers.Dense(32768, activation='sigmoid')(dd2) # Build and compile ,model mdl = keras.models.Model(x, y) mdl.compile(optimizer='rmsprop', loss='binary_crossentropy') # Make file names weights = pkg_resources.resource_filename('WAnet', 'trained_models/simple_inverse_weights.h5') structure = pkg_resources.resource_filename('WAnet', 'trained_models/simple_inverse_structure.yml') plot = pkg_resources.resource_filename('WAnet', 'figures/simple_inverse.eps') # Save model structure and start training x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(new_curves, new_geometry, shuffle=False) if save_results: mdl.fit(new_curves, new_geometry, verbose=VERBOSE, epochs=epochs, shuffle=False, validation_data=(x_test, y_test), callbacks=[keras.callbacks.ModelCheckpoint(filepath=weights, verbose=VERBOSE, save_best_only=True)]) # Save decoder structure and weights temp = open(structure, 'w') temp.write(mdl.to_yaml()) temp.close() else: mdl.fit(new_curves, new_geometry, verbose=VERBOSE, epochs=epochs, shuffle=False, validation_data=(x_test, y_test)) if print_network: keras.utils.plot_model(mdl, to_file=plot, show_shapes=True) # Final check on metrics mdl.load_weights(weights) y_pred = mdl.predict(x_test) mse = keras.backend.mean(keras.losses.binary_crossentropy(y_pred, y_test)).eval() y_pred.fill(numpy.mean(x_test.flatten())) s2 = keras.backend.mean(keras.losses.binary_crossentropy(y_pred, y_test)).eval() r2 = 1-mse/s2 print("Final BCE: "+str(mse)) print("Final S2: "+str(s2)) print("Final R2: "+str(r2)) return r2 def train_simple_forward_network(epochs, save_results, print_network): curves, geometry, S, N, D, F, G, new_curves, new_geometry = load_data() # Define model x = keras.layers.Input(shape=(32768,)) de1 = keras.layers.Dense(3072, activation='relu')(x) de2 = keras.layers.Dense(1536, activation='relu')(de1) con = keras.layers.Dense(768, activation='relu')(de2) dd2 = keras.layers.Dense(384, activation='relu')(con) y = keras.layers.Dense(192, activation='sigmoid')(dd2) # Build and compile ,model mdl = keras.models.Model(x, y) mdl.compile(optimizer='rmsprop', loss='mse') # Make file names weights = pkg_resources.resource_filename('WAnet', 'trained_models/simple_forward_weights.h5') structure = pkg_resources.resource_filename('WAnet', 'trained_models/simple_forward_structure.yml') plot = pkg_resources.resource_filename('WAnet', 'figures/simple_forward.eps') # Save model structure and start training x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(new_geometry, new_curves, shuffle=False) if save_results: mdl.fit(x_train, y_train, verbose=VERBOSE, epochs=epochs, shuffle=False, validation_data=(x_test, y_test), callbacks=[keras.callbacks.ModelCheckpoint(filepath=weights, verbose=VERBOSE, save_best_only=True)]) # Save decoder structure and weights temp = open(structure, 'w') temp.write(mdl.to_yaml()) temp.close() else: mdl.fit(new_geometry, new_curves, verbose=VERBOSE, epochs=epochs, shuffle=False, validation_data=(x_test, y_test)) if print_network: keras.utils.plot_model(mdl, to_file=plot, show_shapes=True) # mdl.load_weights(weights) y_pred = mdl.predict(x_test) s2 = numpy.mean(numpy.power(numpy.mean(y_test.flatten()) - y_test.flatten(), 2)) mse = keras.backend.mean(keras.losses.mean_squared_error(y_pred, y_test)).eval() r2 = 1 - mse / s2 print("Final MSE: " + str(mse)) print("Final S2: " + str(s2)) print("Final R2: " + str(r2)) return r2

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0.69876

3,151

23,058

4.87496

0.074897

0.031639

0.05859

0.082026

0.960875

0.95736

0.952803

0.935551

0.931254

0

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0.171871

23,058

507

167

45.47929

0.791935

0.071645

0

0.70028

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0.047298

0

1

0.042017

false

0

0.014006

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0.098039

0.084034

0

null

0

1

0

1

0

null

0

7

763e9aee578d7770d8934bb15401538afa02f839

1,067

py

Python

tests/integrate/test_login.py

NTUT-108-SE/CMS-Backend

1daa37960ba61f935da5174516f0a2e411b68706

[ "MIT" ]

null

tests/integrate/test_login.py

NTUT-108-SE/CMS-Backend

1daa37960ba61f935da5174516f0a2e411b68706

[ "MIT" ]

null

tests/integrate/test_login.py

NTUT-108-SE/CMS-Backend

1daa37960ba61f935da5174516f0a2e411b68706

[ "MIT" ]

1

2019-10-12T02:48:16.000Z

import pytest def test_login_failed(user_client): res = user_client.post("/login", data={'{"email": "admin@gmail.com", "password": "asd" }': ''}) assert res.status_code == 401 def test_login_None(user_client): res = user_client.post("/login", data={'{"email": "admin@gmail.com" }': ''}) assert res.status_code == 401 def test_login(user_client): res = user_client.post( "/login", data={'{"email": "admin@gmail.com", "password": "admin" }': ''} ) assert res.status_code == 200 assert res.json['user']['email'] == "admin@gmail.com" def test_logout(user_client): test_login(user_client) res = user_client.get("/logout") assert res.status_code == 200 def test_logout_before_login(user_client): res = user_client.get("/logout") assert res.status_code == 401 def test_check_failed(user_client): res = user_client.get("/check") assert res.status_code == 401 def test_check_failed(user_client): test_login(user_client) res = user_client.get("/check") assert res.status_code == 200

25.404762

99

0.663543

148

1,067

4.527027

0.189189

0.238806

0.135821

0.177612

0.846269

0.804478

0.795522

0.69403

0

0.023756

0.171509

1,067

41

100

26.02439

0.734163

0

0.555556

0

0.182755

0

0.296296

1

0.259259

false

0.074074

0.037037

0

0.296296

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null

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1

0

null

0

1

0

1

0

9

769a2a877b701c243cbc22ad5356f2028e91a22f

11,808

py

Python

test/test_raw_data_manifest_manager.py

feiga/fedlearner

99a19934b872a9fba6d85ae018b0ec145612fbca

[ "Apache-2.0" ]

null

test/test_raw_data_manifest_manager.py

feiga/fedlearner

99a19934b872a9fba6d85ae018b0ec145612fbca

[ "Apache-2.0" ]

null

test/test_raw_data_manifest_manager.py

feiga/fedlearner

99a19934b872a9fba6d85ae018b0ec145612fbca

[ "Apache-2.0" ]

1

2020-04-09T07:50:55.000Z

# Copyright 2020 The FedLearner Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # coding: utf-8 import unittest from fedlearner.common import etcd_client from fedlearner.common import data_join_service_pb2 as dj_pb from fedlearner.common import common_pb2 as common_pb from fedlearner.data_join import raw_data_manifest_manager class TestRawDataManifestManager(unittest.TestCase): def test_raw_data_manifest_manager(self): cli = etcd_client.EtcdClient('test_cluster', 'localhost:2379', 'fedlearner', True) partition_num = 4 rank_id = 2 data_source = common_pb.DataSource() data_source.data_source_meta.name = "milestone-x" data_source.data_source_meta.partition_num = partition_num data_source.role = common_pb.FLRole.Leader cli.delete_prefix(data_source.data_source_meta.name) manifest_manager = raw_data_manifest_manager.RawDataManifestManager( cli, data_source) manifest_map = manifest_manager.list_all_manifest() for i in range(partition_num): self.assertTrue(i in manifest_map) self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.UnSynced ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, -1) self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.UnJoined ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, -1) self.assertFalse(manifest_map[i].finished) manifest = manifest_manager.alloc_sync_exampld_id(rank_id) self.assertNotEqual(manifest, None) partition_id = manifest.partition_id manifest_map = manifest_manager.list_all_manifest() for i in range(partition_num): self.assertTrue(i in manifest_map) if i != partition_id: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.UnSynced ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, -1) self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.UnJoined ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, -1) else: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.Syncing ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, rank_id) self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.UnJoined ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, -1) self.assertFalse(manifest_map[i].finished) partition_id2 = 3 - partition_id rank_id2 = 100 manifest = manifest_manager.alloc_join_example(rank_id2, partition_id2) manifest_map = manifest_manager.list_all_manifest() for i in range(partition_num): self.assertTrue(i in manifest_map) if i == partition_id: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.Syncing ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, rank_id) else: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.UnSynced ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, -1) if i == partition_id2: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.Joining ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, rank_id2) else: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.UnJoined ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, -1) self.assertFalse(manifest_map[i].finished) self.assertRaises(Exception, manifest_manager.finish_join_example, rank_id, partition_id) self.assertRaises(Exception, manifest_manager.finish_join_example, rank_id2, partition_id2) self.assertRaises(Exception, manifest_manager.finish_sync_example_id, -rank_id, partition_id) self.assertRaises(Exception, manifest_manager.finish_sync_example_id, rank_id2, partition_id2) rank_id3 = 0 manifest = manifest_manager.alloc_join_example(rank_id3, partition_id) manifest_map = manifest_manager.list_all_manifest() for i in range(partition_num): self.assertTrue(i in manifest_map) if i == partition_id: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.Syncing ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, rank_id) else: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.UnSynced ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, -1) if i == partition_id: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.Joining ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, rank_id3) elif i == partition_id2: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.Joining ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, rank_id2) else: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.UnJoined ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, -1) self.assertFalse(manifest_map[i].finished) self.assertRaises(Exception, manifest_manager.finish_sync_example_id, rank_id, partition_id) self.assertRaises(Exception, manifest_manager.add_raw_data, partition_id, ['a', 'a', 'b'], False) manifest_manager.add_raw_data(partition_id, ['a', 'a', 'b'], True) manifest = manifest_manager.get_manifest(partition_id) self.assertEqual(manifest.next_process_index, 2) manifest_manager.add_raw_data(partition_id, ['a', 'a', 'b', 'c', 'd'], True) manifest_map = manifest_manager.list_all_manifest() for i in range(partition_num): self.assertTrue(i in manifest_map) if i == partition_id: self.assertEqual(manifest_map[i].next_process_index, 4) else: self.assertEqual(manifest_map[i].next_process_index, 0) manifest_manager.finish_raw_data(partition_id) manifest_manager.finish_raw_data(partition_id) self.assertRaises(Exception, manifest_manager.add_raw_data, partition_id, 200) manifest_manager.finish_sync_example_id(rank_id, partition_id) manifest_manager.finish_sync_example_id(rank_id, partition_id) manifest_map = manifest_manager.list_all_manifest() for i in range(data_source.data_source_meta.partition_num): self.assertTrue(i in manifest_map) if i == partition_id: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.Synced ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, rank_id) self.assertTrue(manifest_map[i].finished) else: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.UnSynced ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, -1) if i == partition_id: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.Joining ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, rank_id3) elif i == partition_id2: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.Joining ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, rank_id2) else: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.UnJoined ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, -1) manifest_manager.finish_join_example(rank_id3, partition_id) manifest_manager.finish_join_example(rank_id3, partition_id) manifest_map = manifest_manager.list_all_manifest() for i in range(data_source.data_source_meta.partition_num): self.assertTrue(i in manifest_map) if i == partition_id: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.Synced ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, rank_id) else: self.assertEqual( manifest_map[i].sync_example_id_rep.state, dj_pb.SyncExampleIdState.UnSynced ) self.assertEqual(manifest_map[i].sync_example_id_rep.rank_id, -1) if i == partition_id: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.Joined ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, rank_id3) elif i == partition_id2: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.Joining ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, rank_id2) else: self.assertEqual( manifest_map[i].join_example_rep.state, dj_pb.JoinExampleState.UnJoined ) self.assertEqual(manifest_map[i].join_example_rep.rank_id, -1) cli.destory_client_pool() if __name__ == '__main__': unittest.main()

46.488189

86

0.607808

1,332

11,808

5.045796

0.120871

0.116203

0.101771

0.201161

0.805832

0.800774

0.787383

0.761494

0.752715

0.748847

0

0.007935

0.316904

11,808

253

87

46.671937

0.825316

0.05039

0

0.701754

0

0.005894

0

0.320175

1

0.004386

false

0

0.02193

0

0.030702

0

null

0

1

0

1

0

null

0

8

76bce575ea23f076f84a05c65a04ffa3300bf4ad

2,697

py

Python

utils/utils.py

dawoeh/BioMedRxiv_API

27ca2f42466ffc5a7c0a46215a9df73fc5a9abd3

[ "MIT" ]

null

utils/utils.py

dawoeh/BioMedRxiv_API

27ca2f42466ffc5a7c0a46215a9df73fc5a9abd3

[ "MIT" ]

null

utils/utils.py

dawoeh/BioMedRxiv_API

27ca2f42466ffc5a7c0a46215a9df73fc5a9abd3

[ "MIT" ]

null

import requests import json from time import sleep import tqdm import math import pandas as pd def date_rxiv(server, from_date, to_date, result_start=0): data = pd.DataFrame() pbar = None while True: response = requests.get(f'https://api.biorxiv.org/details/{server}/{from_date}/{to_date}/{result_start}') doc = response.json() result_count = len(doc['collection']) batch = 100 if pbar is None: pbar = tqdm.tqdm(total= math.ceil(int(doc['messages'][0]['total'])/batch)) if result_count == 0: break data = data.append(pd.DataFrame(doc['collection'])).reset_index(drop=True) result_start += 100 pbar.update(1) sleep(0.2) pbar.close() return data def article_detail(server, doi): data = pd.DataFrame() response = requests.get(f'https://api.biorxiv.org/details/{server}/{doi}') doc = response.json() data = data.append(pd.DataFrame(doc['collection'])).reset_index(drop=True) return data def date_published_article(from_date, to_date, result_start=0): data = pd.DataFrame() pbar = None while True: response = requests.get(f'https://api.biorxiv.org/pub/{from_date}/{to_date}/{result_start}') doc = response.json() result_count = len(doc['collection']) batch = 100 if pbar is None: pbar = tqdm.tqdm(total= math.ceil(int(doc['messages'][0]['total'])/batch)) if result_count == 0: break data = data.append(pd.DataFrame(doc['collection'])).reset_index(drop=True) result_start += batch pbar.update(1) sleep(0.2) pbar.close() return data def date_publisher_detail(publisher_id, from_date, to_date, result_start=0): data = pd.DataFrame() pbar = None while True: response = requests.get(f'https://api.biorxiv.org/publisher/{publisher_id}/{from_date}/{to_date}/{result_start}') doc = response.json() result_count = len(doc['collection']) batch = 100 if pbar is None: pbar = tqdm.tqdm(total= math.ceil(int(doc['messages'][0]['total'])/batch)) if result_count == 0: break data = data.append(pd.DataFrame(doc['collection'])).reset_index(drop=True) result_start += batch pbar.update(1) sleep(0.2) pbar.close() return data def biorxiv_stats(interval = 'm'): data = pd.DataFrame() response = requests.get(f'https://api.biorxiv.org/sum/{interval}') doc = response.json() data = data.append(pd.DataFrame(doc['bioRxiv content statistics'])).reset_index(drop=True) return data

34.139241

121

0.618465

356

2,697

4.570225

0.191011

0.067609

0.036878

0.051629

0.859865

0.836509

0.832821

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1

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null

0

7

4f5df69aa9de018222c7713fcedc0ff6c1f4b20e

710

py

Python

lib/workflow/rule/tag_multi.py

auho/python-ETL

761589814b04e076ba6fa1c0e64b83ce62ce8556

[ "Apache-2.0" ]

null

lib/workflow/rule/tag_multi.py

auho/python-ETL

761589814b04e076ba6fa1c0e64b83ce62ce8556

[ "Apache-2.0" ]

null

lib/workflow/rule/tag_multi.py

auho/python-ETL

761589814b04e076ba6fa1c0e64b83ce62ce8556

[ "Apache-2.0" ]

null

from . import tag class TagRule(tag.TagRule): def _main(self): self._keywordFunList.append(tag.symbol_underline_fun) def get_keys(self): return [self._keywordName, self._get_alias(f"{self._name}_keyword_num")] + self.get_tags_keys() def tag_insert(self, content): return self._tag_multi_insert(content=content) class TagRuleEveryKeyword(tag.TagRule): def _main(self): self._keywordFunList.append(tag.symbol_underline_fun) def get_keys(self): return [self._keywordName, self._get_alias(f"{self._name}_keyword_num")] + self.get_tags_keys() def tag_insert(self, content): return self._tag_multi_insert_every_keyword(content=content)

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8

96e50fb0fcee2f9625b7316c1e0d1cda524f9e76

6,229

py

Python

tikv_client/__init__.py

gotoxu/client-py

1f3158e9a0a88e10afb89078b15ddf1b1d11c7dc

[ "Apache-2.0" ]

null

tikv_client/__init__.py

gotoxu/client-py

1f3158e9a0a88e10afb89078b15ddf1b1d11c7dc

[ "Apache-2.0" ]

null

tikv_client/__init__.py

gotoxu/client-py

1f3158e9a0a88e10afb89078b15ddf1b1d11c7dc

[ "Apache-2.0" ]

null

# Copyright 2020 TiKV Project Authors. Licensed under Apache-2.0. import asyncio from . import asynchronous class RawClient: def __init__(self): raise Exception("Please use `RawClient.connect()` instead.") @classmethod def connect(cls, pd_endpoint): event_loop = asyncio.get_event_loop() inner = event_loop.run_until_complete( asynchronous.RawClient.connect(pd_endpoint)) self = cls.__new__(cls) self.inner = inner return self def get(self, key, cf="default"): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.get(key, cf)) def batch_get(self, keys, cf="default"): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.batch_get(keys, cf)) def scan(self, start, end, limit, include_start=True, include_end=False, cf="default"): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.scan(start, end, limit, include_start, include_end, cf)) def scan_keys(self, start, end, limit, include_start=True, include_end=False, cf="default"): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.scan_keys(start, end, limit, include_start, include_end, cf)) def put(self, key, value, cf="default"): event_loop = asyncio.get_event_loop() event_loop.run_until_complete(self.inner.put(key, value, cf)) def batch_put(self, pairs, cf="default"): event_loop = asyncio.get_event_loop() event_loop.run_until_complete(self.inner.put(pairs, cf)) def delete(self, key, cf="default"): event_loop = asyncio.get_event_loop() event_loop.run_until_complete(self.inner.delete(key, cf)) def batch_delete(self, keys, cf="default"): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.batch_delete(keys, cf)) def delete_range(self, start, end=None, include_start=True, include_end=False, cf="default"): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.delete_range(start, end, include_start, include_end, cf)) class TransactionClient: def __init__(self): raise Exception("Please use `TransactionClient.connect()` instead.") @classmethod def connect(cls, pd_endpoint): event_loop = asyncio.get_event_loop() inner = event_loop.run_until_complete( asynchronous.TransactionClient.connect(pd_endpoint)) self = cls.__new__(cls) self.inner = inner return self def begin(self, pessimistic=False): event_loop = asyncio.get_event_loop() transaction = event_loop.run_until_complete( self.inner.begin(pessimistic)) return Transaction(transaction) def current_timestamp(self): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete( self.inner.current_timestamp()) def snapshot(self, timestamp, pessimistic): snapshot = self.inner.snapshot(timestamp, pessimistic) return Snapshot(snapshot) class Snapshot: def __init__(self, inner): self.inner = inner def get(self, key): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.get(key)) def key_exists(self, key): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.key_exists(key)) def batch_get(self, keys): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.batch_get(keys)) def scan(self, start, end, limit, include_start=True, include_end=False): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.scan(start, end, limit, include_start, include_end)) def scan_keys(self, start, end, limit, include_start=True, include_end=False): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.scan_keys(start, end, limit, include_start, include_end)) class Transaction: def __init__(self, inner): self.inner = inner def get(self, key): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.get(key)) def get_for_update(self, key): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.get_for_update(key)) def key_exists(self, key): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.key_exists(key)) def batch_get(self, keys): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.batch_get(keys)) def batch_get_for_update(self, keys): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.batch_get_for_update(keys)) def scan(self, start, end, limit, include_start=True, include_end=False): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.scan(start, end, limit, include_start, include_end)) def scan_keys(self, start, end, limit, include_start=True, include_end=False): event_loop = asyncio.get_event_loop() return event_loop.run_until_complete(self.inner.scan_keys(start, end, limit, include_start, include_end)) def lock_keys(self, keys): event_loop = asyncio.get_event_loop() event_loop.run_until_complete(self.inner.lock_keys(keys)) def put(self, key, value): event_loop = asyncio.get_event_loop() event_loop.run_until_complete(self.inner.put(key, value)) def insert(self, key, value): event_loop = asyncio.get_event_loop() event_loop.run_until_complete(self.inner.insert(key, value)) def delete(self, key): event_loop = asyncio.get_event_loop() event_loop.run_until_complete(self.inner.delete(key)) def commit(self): event_loop = asyncio.get_event_loop() event_loop.run_until_complete(self.inner.commit())

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0.117216

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0.786081

0

0.001196

0.194895

6,229

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0.815354

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0

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null

0

1

0

null

0

1

0

7

8c14f9519e17251dad6656b2f31d302f266612ef

6,701

py

Python

quick_sort2.py

RitRa/Algorithms-project-

d9de6437be9fa3424aeec08cb8cf42bc377c5813

[ "MIT" ]

null

quick_sort2.py

RitRa/Algorithms-project-

d9de6437be9fa3424aeec08cb8cf42bc377c5813

[ "MIT" ]

null

quick_sort2.py

RitRa/Algorithms-project-

d9de6437be9fa3424aeec08cb8cf42bc377c5813

[ "MIT" ]

null

# importing the random numbers from randomnumber import * # Quick Sort def printalistay(alist): return (' '.join(str(i) for i in alist)) def quicksort(alist, i, j): if i < j: pos = partition(alist, i, j) quicksort(alist, i, pos - 1) quicksort(alist, pos + 1, j) def partition(alist, i, j): #pivot = alist[j] # pivot on the last item pivot = alist[int(j/2)] # pivot on the median small = i - 1 for k in range(i, j): if alist[k] <= pivot: small += 1 swap(alist, k, small) swap(alist, j, small + 1) print ("Pivot = " + str(alist[small + 1]), " alist = " + printalistay(alist)) return small + 1 def swap(alist, i, j): alist[i], alist[j] = alist[j], alist[i] #if __name__ == '__main__': # alist = [9, 4, 8, 3, 1, 2, 5] # print (" Initial alistay :",printalistay(alist)) # quicksort(alist, 0, len(alist) - 1) # import time module import time num_runs = 10 results = [] quicksort_avglist = [] def benchmark_quick(): for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist1, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist2, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist3, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist4, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist5, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist6, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist7, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist8, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() quicksort(alist9, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist10, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist11, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist12, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) # round to 3 decimals average = round(average, 3) quicksort_avglist.append(average) for r in range(num_runs): # start timer start_time = time.time() ######## call quick sort quicksort(alist13, 0, len(alist) - 1) end_time = time.time() time_elapsed= end_time - start_time results.append(time_elapsed) b = sum(results) average = (b/num_runs) # round to 3 decimals average = round(average, 3) quicksort_avglist.append(average) print(quicksort_avglist) benchmark_quick()

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8c36d746f722700e291437f166c23acae2412cb6

129,264

py

Python

simplema/jessetkdata/dnafiles/ETH-USDT 2019-12-20 2021-11-12.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

38

2021-09-18T15:33:28.000Z

2022-02-21T17:29:08.000Z

simplema/jessetkdata/dnafiles/ETH-USDT 2019-12-20 2021-11-12.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

4

2022-01-02T14:46:12.000Z

2022-02-16T18:39:41.000Z

simplema/jessetkdata/dnafiles/ETH-USDT 2019-12-20 2021-11-12.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

11

2021-10-19T06:21:43.000Z

2022-02-21T17:29:10.000Z

dnas = [ ['pX3Eo\\]', 38, 146, 1069.71, 38, 26, -27.55, {'qty_to_risk': 7, 'target_pnl': 253, 'stop': 35, 'donchlen': 78, 'treshold': 92, 'ema_fast': 14, 'ema_slow': 40}], ['k[3Eo\\]', 38, 146, 1030.13, 38, 26, -27.55, {'qty_to_risk': 7, 'target_pnl': 267, 'stop': 35, 'donchlen': 78, 'treshold': 92, 'ema_fast': 14, 'ema_slow': 40}], ['kP3Eo\\e', 37, 139, 1082.78, 35, 28, -29.22, {'qty_to_risk': 7, 'target_pnl': 215, 'stop': 35, 'donchlen': 78, 'treshold': 92, 'ema_fast': 14, 'ema_slow': 43}], ['FJa00oP', 28, 98, 365.62, 33, 12, 16.07, {'qty_to_risk': 4, 'target_pnl': 186, 'stop': 140, 'donchlen': 27, 'treshold': 28, 'ema_fast': 18, 'ema_slow': 36}], ['<Q4g6_w', 39, 82, 155.73, 33, 12, -9.72, {'qty_to_risk': 4, 'target_pnl': 220, 'stop': 37, 'donchlen': 161, 'treshold': 34, 'ema_fast': 15, 'ema_slow': 50}], ['vTJpoL_', 30, 128, 1745.08, 35, 14, -19.59, {'qty_to_risk': 8, 'target_pnl': 234, 'stop': 87, 'donchlen': 183, 'treshold': 92, 'ema_fast': 10, 'ema_slow': 41}], ['\\VkQcqv', 33, 84, 413.65, 35, 14, -4.28, {'qty_to_risk': 6, 'target_pnl': 243, 'stop': 163, 'donchlen': 108, 'treshold': 80, 'ema_fast': 19, 'ema_slow': 50}], [':Wso^YR', 33, 113, 346.06, 30, 13, -8.96, {'qty_to_risk': 3, 'target_pnl': 248, 'stop': 181, 'donchlen': 181, 'treshold': 75, 'ema_fast': 13, 'ema_slow': 36}], [']Vdom\\a', 33, 103, 707.66, 33, 12, -28.46, {'qty_to_risk': 6, 'target_pnl': 243, 'stop': 147, 'donchlen': 181, 'treshold': 90, 'ema_fast': 14, 'ema_slow': 42}], ['vP3Ep\\g', 36, 141, 1354.18, 29, 27, -35.49, {'qty_to_risk': 8, 'target_pnl': 215, 'stop': 35, 'donchlen': 78, 'treshold': 93, 'ema_fast': 14, 'ema_slow': 44}], ['7\\lUAmD', 37, 88, 205.96, 28, 14, -14.69, {'qty_to_risk': 3, 'target_pnl': 272, 'stop': 165, 'donchlen': 117, 'treshold': 45, 'ema_fast': 18, 'ema_slow': 31}], ['v[JpoL_', 30, 128, 2365.3, 35, 14, -19.59, {'qty_to_risk': 8, 'target_pnl': 267, 'stop': 87, 'donchlen': 183, 'treshold': 92, 'ema_fast': 10, 'ema_slow': 41}], ['vP3EpJl', 36, 152, 1098.34, 36, 25, -23.1, {'qty_to_risk': 8, 'target_pnl': 215, 'stop': 35, 'donchlen': 78, 'treshold': 93, 'ema_fast': 10, 'ema_slow': 46}], ['[QIuPr7', 36, 110, 1317.14, 15, 13, -40.34, {'qty_to_risk': 6, 'target_pnl': 220, 'stop': 85, 'donchlen': 195, 'treshold': 61, 'ema_fast': 19, 'ema_slow': 27}], ['vXJpoL_', 30, 128, 2498.01, 35, 14, -19.59, {'qty_to_risk': 8, 'target_pnl': 253, 'stop': 87, 'donchlen': 183, 'treshold': 92, 'ema_fast': 10, 'ema_slow': 41}], ['8=Hq`W7', 33, 130, 175.83, 37, 16, 11.82, {'qty_to_risk': 3, 'target_pnl': 125, 'stop': 83, 'donchlen': 185, 'treshold': 77, 'ema_fast': 13, 'ema_slow': 27}], ['Mlo/YnH', 35, 110, 1170.47, 38, 18, 57.63, {'qty_to_risk': 5, 'target_pnl': 348, 'stop': 172, 'donchlen': 25, 'treshold': 70, 'ema_fast': 18, 'ema_slow': 33}], ['DOLnrsd', 39, 87, 351.48, 33, 12, -20.77, {'qty_to_risk': 4, 'target_pnl': 210, 'stop': 92, 'donchlen': 178, 'treshold': 95, 'ema_fast': 19, 'ema_slow': 43}], ['vP3Ea\\l', 35, 137, 1265.15, 30, 26, -31.0, {'qty_to_risk': 8, 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46, 15, 83.7, {'qty_to_risk': 5, 'target_pnl': 153, 'stop': 172, 'donchlen': 81, 'treshold': 23, 'ema_fast': 8, 'ema_slow': 22}], ['OsE\\e=)', 27, 214, 400.37, 45, 33, 66.95, {'qty_to_risk': 5, 'target_pnl': 381, 'stop': 76, 'donchlen': 134, 'treshold': 82, 'ema_fast': 7, 'ema_slow': 21}], ['sXvp5.?', 21, 239, 1362.06, 34, 38, 66.02, {'qty_to_risk': 8, 'target_pnl': 253, 'stop': 188, 'donchlen': 183, 'treshold': 33, 'ema_fast': 3, 'ema_slow': 29}], ['sXvp5.=', 21, 239, 1362.06, 34, 38, 66.02, {'qty_to_risk': 8, 'target_pnl': 253, 'stop': 188, 'donchlen': 183, 'treshold': 33, 'ema_fast': 3, 'ema_slow': 29}], ['E8kw9)r', 21, 218, 178.97, 27, 29, 31.01, {'qty_to_risk': 4, 'target_pnl': 101, 'stop': 163, 'donchlen': 200, 'treshold': 37, 'ema_fast': 2, 'ema_slow': 48}], ['vuZpo._', 22, 210, 2164.98, 32, 28, 22.26, {'qty_to_risk': 8, 'target_pnl': 391, 'stop': 124, 'donchlen': 183, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 41}], ['v53so1l', 30, 181, 981.66, 31, 29, -24.56, {'qty_to_risk': 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'donchlen': 183, 'treshold': 33, 'ema_fast': 4, 'ema_slow': 32}], ['sXvp5.2', 23, 266, 2518.63, 23, 47, 26.2, {'qty_to_risk': 8, 'target_pnl': 253, 'stop': 188, 'donchlen': 183, 'treshold': 33, 'ema_fast': 3, 'ema_slow': 25}], ['vdOpoL6', 31, 147, 2028.9, 36, 19, 22.31, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 99, 'donchlen': 183, 'treshold': 92, 'ema_fast': 10, 'ema_slow': 26}], ['kd3E:H]', 36, 132, 1241.91, 47, 17, -2.14, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 78, 'treshold': 38, 'ema_fast': 9, 'ema_slow': 40}], ['nj3U:WD', 38, 107, 724.13, 40, 15, -14.5, {'qty_to_risk': 7, 'target_pnl': 338, 'stop': 35, 'donchlen': 117, 'treshold': 38, 'ema_fast': 13, 'ema_slow': 31}], ['sXvp5.@', 21, 232, 1352.84, 35, 34, 71.08, {'qty_to_risk': 8, 'target_pnl': 253, 'stop': 188, 'donchlen': 183, 'treshold': 33, 'ema_fast': 3, 'ema_slow': 30}], ['sXvp5.A', 21, 232, 1352.84, 35, 34, 71.08, {'qty_to_risk': 8, 'target_pnl': 253, 'stop': 188, 'donchlen': 183, 'treshold': 33, 'ema_fast': 3, 'ema_slow': 30}], ['kdGpo)l', 21, 242, 1040.83, 28, 32, 27.1, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 81, 'donchlen': 183, 'treshold': 92, 'ema_fast': 2, 'ema_slow': 46}], ['vdds51[', 27, 158, 3339.23, 30, 20, 26.3, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 147, 'donchlen': 190, 'treshold': 33, 'ema_fast': 4, 'ema_slow': 40}], ['vdJpo+_', 22, 211, 1407.51, 32, 28, 26.14, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 87, 'donchlen': 183, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 41}], ['veZpo._', 22, 210, 1919.95, 32, 28, 22.26, {'qty_to_risk': 8, 'target_pnl': 315, 'stop': 124, 'donchlen': 183, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 41}], ['vkZpo._', 22, 210, 1835.44, 32, 28, 22.26, {'qty_to_risk': 8, 'target_pnl': 343, 'stop': 124, 'donchlen': 183, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 41}], ['vdqpo.^', 22, 208, 1750.25, 32, 28, 22.26, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 176, 'donchlen': 183, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 41}], 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37, 27, -6.14, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 93, 'ema_fast': 4, 'ema_slow': 43}], ['kd9?o1i', 29, 193, 700.03, 31, 29, -13.26, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 49, 'donchlen': 64, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 45}], ['vd:s51l', 28, 153, 1799.33, 25, 20, -22.9, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 51, 'donchlen': 190, 'treshold': 33, 'ema_fast': 4, 'ema_slow': 46}], ['k]3wo1r', 31, 174, 1170.04, 27, 29, -36.92, {'qty_to_risk': 7, 'target_pnl': 277, 'stop': 35, 'donchlen': 200, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 48}], ['k]3vo1r', 31, 174, 1168.27, 27, 29, -36.92, {'qty_to_risk': 7, 'target_pnl': 277, 'stop': 35, 'donchlen': 198, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 48}], ['vd3E>1l', 32, 165, 1310.33, 44, 25, 14.05, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 78, 'treshold': 42, 'ema_fast': 4, 'ema_slow': 46}], ['kU3ko,r', 27, 208, 737.15, 32, 28, -3.8, {'qty_to_risk': 7, 'target_pnl': 239, 'stop': 35, 'donchlen': 171, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 48}], ['pd3wo1j', 30, 185, 1206.69, 33, 27, -9.76, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 200, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 45}], ['vd3so1j', 30, 184, 1365.16, 33, 27, -13.57, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 45}], ['vd3so1i', 30, 184, 1365.16, 33, 27, -13.57, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 45}], ['vd3sf1l', 30, 178, 1109.72, 31, 29, -20.9, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 83, 'ema_fast': 4, 'ema_slow': 46}], ['KecdnJ/', 29, 150, 359.54, 35, 20, 12.82, {'qty_to_risk': 5, 'target_pnl': 315, 'stop': 144, 'donchlen': 154, 'treshold': 91, 'ema_fast': 10, 'ema_slow': 24}], ['vw3so1l', 30, 181, 1364.12, 31, 29, -20.9, {'qty_to_risk': 8, 'target_pnl': 400, 'stop': 35, 'donchlen': 190, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vkop5.7', 22, 251, 2419.47, 29, 41, 52.61, {'qty_to_risk': 8, 'target_pnl': 343, 'stop': 172, 'donchlen': 183, 'treshold': 33, 'ema_fast': 3, 'ema_slow': 27}], ['vdfp5.F', 21, 224, 1363.92, 31, 32, 47.43, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 151, 'donchlen': 183, 'treshold': 33, 'ema_fast': 3, 'ema_slow': 32}], ['vdqpo.X', 22, 215, 1628.64, 33, 27, 42.68, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 176, 'donchlen': 183, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 39}], ['vdqpo.Y', 22, 215, 1628.64, 33, 27, 42.68, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 176, 'donchlen': 183, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 39}], ['vj3?o1l', 31, 198, 1054.59, 48, 35, 35.52, {'qty_to_risk': 8, 'target_pnl': 338, 'stop': 35, 'donchlen': 64, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vi3?o1l', 31, 198, 1054.59, 48, 35, 35.52, {'qty_to_risk': 8, 'target_pnl': 334, 'stop': 35, 'donchlen': 64, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['kt3qo1l', 30, 182, 979.79, 32, 28, -9.72, {'qty_to_risk': 7, 'target_pnl': 386, 'stop': 35, 'donchlen': 185, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vd3Bp1l', 31, 194, 1182.71, 47, 34, 35.26, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 71, 'treshold': 93, 'ema_fast': 4, 'ema_slow': 46}], ['vd3?o/l', 31, 198, 1107.42, 48, 35, 35.52, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 64, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vd3?o1l', 31, 198, 1107.42, 48, 35, 35.52, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 64, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vd3?u1l', 31, 199, 1081.5, 48, 35, 35.52, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 64, 'treshold': 98, 'ema_fast': 4, 'ema_slow': 46}], ['vm3?o1l', 31, 198, 1054.59, 48, 35, 35.52, {'qty_to_risk': 8, 'target_pnl': 353, 'stop': 35, 'donchlen': 64, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], 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{'qty_to_risk': 7, 'target_pnl': 319, 'stop': 35, 'donchlen': 185, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['gd3qo1l', 30, 182, 1025.62, 32, 28, -9.72, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 185, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['od3qo1l', 30, 182, 1025.62, 32, 28, -9.72, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 185, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['ed3qo1l', 30, 182, 1025.62, 32, 28, -9.72, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 185, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['kd3qu1l', 30, 183, 1001.62, 32, 28, -9.72, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 185, 'treshold': 98, 'ema_fast': 4, 'ema_slow': 46}], ['kr3qo1l', 30, 182, 979.79, 32, 28, -9.72, {'qty_to_risk': 7, 'target_pnl': 376, 'stop': 35, 'donchlen': 185, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['ad3wp1l', 30, 182, 890.24, 31, 29, -12.58, {'qty_to_risk': 6, 'target_pnl': 310, 'stop': 35, 'donchlen': 200, 'treshold': 93, 'ema_fast': 4, 'ema_slow': 46}], ['vd3no1l', 30, 182, 1372.66, 32, 28, -13.44, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 178, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vd3qo1l', 30, 182, 1366.79, 32, 28, -13.44, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 185, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vd3po/l', 30, 182, 1366.82, 32, 28, -13.44, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 183, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vd3po2l', 30, 182, 1366.82, 32, 28, -13.44, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 183, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['vd3do1l', 29, 181, 793.58, 29, 27, -15.57, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 154, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 46}], ['jd3so1l', 30, 181, 1066.14, 31, 29, -16.75, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 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{'qty_to_risk': 8, 'target_pnl': 310, 'stop': 33, 'donchlen': 190, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 41}], ['kd3to1]', 29, 185, 1289.24, 35, 28, -8.35, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 193, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ['pd3to1]', 29, 185, 1289.24, 35, 28, -8.35, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 193, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ['hd3so1]', 29, 185, 1036.82, 35, 28, -8.35, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ['gd3so1]', 29, 185, 1036.82, 35, 28, -8.35, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ['kd3so1]', 29, 185, 1036.82, 35, 28, -8.35, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ['kd3so0]', 29, 185, 1036.82, 35, 28, -8.35, {'qty_to_risk': 7, 'target_pnl': 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'treshold': 33, 'ema_fast': 3, 'ema_slow': 22}], ['kv3ko,r', 27, 208, 698.51, 32, 28, -3.8, {'qty_to_risk': 7, 'target_pnl': 395, 'stop': 35, 'donchlen': 171, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 48}], ['eeUY+N,', 29, 113, 1095.42, 40, 10, 22.03, {'qty_to_risk': 7, 'target_pnl': 315, 'stop': 113, 'donchlen': 127, 'treshold': 23, 'ema_fast': 11, 'ema_slow': 22}], ['kd9?B1H', 29, 194, 1795.09, 40, 25, 19.98, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 49, 'donchlen': 64, 'treshold': 46, 'ema_fast': 4, 'ema_slow': 33}], ['p43vo1]', 29, 186, 940.19, 35, 28, -12.05, {'qty_to_risk': 7, 'target_pnl': 82, 'stop': 35, 'donchlen': 198, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ['pd6vo1]', 29, 185, 871.18, 25, 27, 23.08, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 42, 'donchlen': 198, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ['kd6so1]', 29, 185, 973.11, 25, 27, 19.67, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 42, 'donchlen': 190, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ['XlIr0/7', 22, 209, 692.47, 31, 29, 29.78, {'qty_to_risk': 6, 'target_pnl': 348, 'stop': 85, 'donchlen': 188, 'treshold': 28, 'ema_fast': 4, 'ema_slow': 27}], ['kd9?J1H', 30, 203, 1381.71, 37, 27, 7.95, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 49, 'donchlen': 64, 'treshold': 54, 'ema_fast': 4, 'ema_slow': 33}], ['kf3ko,r', 27, 208, 744.96, 32, 28, -3.8, {'qty_to_risk': 7, 'target_pnl': 319, 'stop': 35, 'donchlen': 171, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 48}], ['kd3ko,r', 27, 208, 734.11, 32, 28, -3.8, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 171, 'treshold': 92, 'ema_fast': 3, 'ema_slow': 48}], ['kd9?M1H', 29, 204, 1381.6, 37, 27, 7.95, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 49, 'donchlen': 64, 'treshold': 57, 'ema_fast': 4, 'ema_slow': 33}], ['pd3vD1]', 29, 175, 965.23, 37, 27, -4.28, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 198, 'treshold': 48, 'ema_fast': 4, 'ema_slow': 40}], ['vd3soF)', 33, 187, 1699.13, 35, 34, 7.36, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 92, 'ema_fast': 9, 'ema_slow': 21}], ['kd3sO1]', 28, 177, 845.92, 35, 28, -8.35, {'qty_to_risk': 7, 'target_pnl': 310, 'stop': 35, 'donchlen': 190, 'treshold': 59, 'ema_fast': 4, 'ema_slow': 40}], ['vd3p4L+', 34, 141, 1312.64, 40, 20, 12.37, {'qty_to_risk': 8, 'target_pnl': 310, 'stop': 35, 'donchlen': 183, 'treshold': 32, 'ema_fast': 10, 'ema_slow': 22}], ['p13vo1]', 29, 186, 663.6, 35, 28, -1.65, {'qty_to_risk': 7, 'target_pnl': 68, 'stop': 35, 'donchlen': 198, 'treshold': 92, 'ema_fast': 4, 'ema_slow': 40}], ]

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Python

tests/test_transform.py

brandonschabell/datetransform

7331185d854f14734a33ee00a84367d33c2aada0

[ "MIT" ]

1

2020-01-15T02:05:16.000Z

tests/test_transform.py

brandonschabell/datetransform

7331185d854f14734a33ee00a84367d33c2aada0

[ "MIT" ]

3

2020-04-22T20:48:22.000Z

2020-05-04T23:38:32.000Z

tests/test_transform.py

brandonschabell/datetransform

7331185d854f14734a33ee00a84367d33c2aada0

[ "MIT" ]

null

import pandas as pd from datetransform import transform def test_add_date_features(): df = pd.DataFrame({'dateCol': ['2019-08-09 16:39:47']}) df = transform.add_date_features(df, 'dateCol') assert df.columns.tolist() == ['dateCol', 'dateColYear', 'dateColMonth', 'dateColWeek', 'dateColDay', 'dateColDayOfWeek', 'dateColDayOfYear', 'dateColIsMonthEnd', 'dateColIsMonthStart', 'dateColIsQuarterEnd', 'dateColIsQuarterStart', 'dateColIsYearEnd', 'dateColIsYearStart', 'dateColHour', 'dateColMinute', 'dateColSecond'] def test_inplace_transform(): df = pd.DataFrame({'dateCol': ['2019-08-09 16:39:47']}) transform.add_date_features(df, 'dateCol', inplace=True) assert df.columns.tolist() == ['dateCol', 'dateColYear', 'dateColMonth', 'dateColWeek', 'dateColDay', 'dateColDayOfWeek', 'dateColDayOfYear', 'dateColIsMonthEnd', 'dateColIsMonthStart', 'dateColIsQuarterEnd', 'dateColIsQuarterStart', 'dateColIsYearEnd', 'dateColIsYearStart', 'dateColHour', 'dateColMinute', 'dateColSecond'] def test_not_inplace_transform(): df = pd.DataFrame({'dateCol': ['2019-08-09 16:39:47']}) transform.add_date_features(df, 'dateCol') assert df.columns.tolist() == ['dateCol']

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py

Python

examples/fitzhugh-nagumo/visualize.py

JamesBrofos/Thresholds-in-Hamiltonian-Monte-Carlo

7ee1b530db0eb536666dbc872fbf8200e53dd49b

[ "MIT" ]

1

2021-11-23T15:40:07.000Z

examples/fitzhugh-nagumo/visualize.py

JamesBrofos/Thresholds-in-Hamiltonian-Monte-Carlo

7ee1b530db0eb536666dbc872fbf8200e53dd49b

[ "MIT" ]

null

examples/fitzhugh-nagumo/visualize.py

JamesBrofos/Thresholds-in-Hamiltonian-Monte-Carlo

7ee1b530db0eb536666dbc872fbf8200e53dd49b

[ "MIT" ]

null

import glob import os import pickle import matplotlib.pyplot as plt import numpy as np import scipy.stats as spst from scipy.integrate import odeint from hmc import summarize from hmc.applications.fitzhugh_nagumo import fn_dynamics from load_data import load_data def euclidean_samples(): num_samples = [1000, 10000, 100000] euclid = {} for ns in num_samples: d = {} fns = sorted(glob.glob(os.path.join('samples', '*num-samples-{}-*euclidean*'.format(ns)))) for f in fns: ss = f.split('-step-size-')[1].split('-')[0] ss = float(ss) with open(f, 'rb') as g: d[ss] = pickle.load(g) euclid[ns] = d return euclid def iid_samples(): iid = [] with open(os.path.join('data', 'samples.pkl'), 'rb') as f: iid.append(pickle.load(f)) with open(os.path.join('data', 'samples-{}.pkl'.format(1)), 'rb') as f: iid.append(pickle.load(f)) return iid def riemannian_samples(newton_momentum=False, newton_position=False): num_samples = [1000, 10000, 100000] rmn = {} for ns in num_samples: d = {} fns = sorted(glob.glob(os.path.join('samples', '*num-steps-6*-num-samples-{}-*riemannian*partial-momentum-0.0*-correct-True*newton-momentum-{}*newton-position-{}*'.format(ns, newton_momentum, newton_position)))) for f in fns: t = f.split('-thresh-')[1].split('-m')[0] t = float(t) with open(f, 'rb') as g: d[t] = pickle.load(g) rmn[ns] = d return rmn def fitzhugh_nagumo(): euclid = euclidean_samples()[100000] rmn = riemannian_samples()[100000] y, time, sigma, state = load_data() rkeys = sorted(rmn.keys(), reverse=False) ekeys = sorted(euclid.keys(), reverse=False) m = len(rkeys) + len(ekeys) fig = plt.figure(figsize=(30, 5)) for i, t in enumerate(ekeys): s = euclid[t]['samples'] yh = [] for j in range(0, len(s), 100): params = tuple(s[j]) yh.append(odeint(fn_dynamics, state, time, params)) yh = np.array(yh) ax = fig.add_subplot(1, m, i+1) ax.plot(time, yh[..., 0].T, '-', color='tab:blue', alpha=0.1) ax.plot(time, yh[..., 1].T, '-', color='tab:orange', alpha=0.1) ax.plot(time, y[..., 0], '.', color='tab:blue', markersize=2) ax.plot(time, y[..., 1], '.', color='tab:orange', markersize=2) ax.set_ylim((-3, 3)) ax.set_title('Euclid. {:.0e}'.format(t), fontsize=35) ax.axes.get_xaxis().set_visible(False) ax.axes.get_yaxis().set_visible(False) for i, t in enumerate(rkeys): s = rmn[t]['samples'] yh = [] for j in range(0, len(s), 100): params = tuple(s[j]) yh.append(odeint(fn_dynamics, state, time, params)) yh = np.array(yh) ax = fig.add_subplot(1, m, i+len(ekeys)+1) ax.plot(time, yh[..., 0].T, '-', color='tab:blue', alpha=0.1) ax.plot(time, yh[..., 1].T, '-', color='tab:orange', alpha=0.1) ax.plot(time, y[..., 0], '.', color='tab:blue', markersize=2) ax.plot(time, y[..., 1], '.', color='tab:orange', markersize=2) ax.set_ylim((-3, 3)) ax.set_title('Thresh. {:.0e}'.format(t), fontsize=35) ax.axes.get_xaxis().set_visible(False) ax.axes.get_yaxis().set_visible(False) fig.tight_layout() fig.savefig(os.path.join('images', 'fitzhugh-nagumo.png')) def effective_sample_size(): euclid = euclidean_samples()[100000] rmn = riemannian_samples()[100000] ekeys = sorted(euclid.keys(), reverse=False) rkeys = sorted(rmn.keys(), reverse=False) labels = ['Euclidean {}'.format(t) for t in ekeys] + ['Threshold {:.0e}'.format(t) for t in rkeys] fig = plt.figure(figsize=(10, 4)) ax = fig.add_subplot(111) num_breaks = 20 ess = {} for t in ekeys: breaks = np.split(euclid[t]['samples'], num_breaks, axis=0) k = 'euclid-{}'.format(t) ess[k] = [] for i, b in enumerate(breaks): metrics = summarize(b) m = metrics['ess'].min() ess[k].append(m) ax.violinplot([ess[k] for k in ess.keys()], showmeans=True, showmedians=True, showextrema=False) ess = {} for t in rkeys: breaks = np.split(rmn[t]['samples'], num_breaks, axis=0) k = 'rmn-{}'.format(t) ess[k] = [] for i, b in enumerate(breaks): metrics = summarize(b) m = metrics['ess'].min() ess[k].append(m) vpb = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 2, showmeans=True, showmedians=True, showextrema=False) ax.set_xticks(np.arange(1, len(labels) + 1)) ax.set_xticklabels(['' for l in labels]) ax.set_xticklabels(labels) ax.set_xlim(0.25, len(labels) + 0.75) for tick in ax.get_xticklabels(): tick.set_rotation(90) ax.axvline(len(ekeys) + 0.5, color='black', linestyle='--') ax.set_xlabel('') ax.set_ylabel('Min. ESS', fontsize=16) ax.tick_params(axis='y', labelsize=16) ax.tick_params(axis='x', labelsize=16) ax.grid(linestyle=':') fig.tight_layout() fig.savefig(os.path.join('images', 'minimum-ess.pdf')) def effective_sample_size_per_second(): euclid = euclidean_samples()[100000] rmn = riemannian_samples()[100000] nm_rmn = riemannian_samples(True)[100000] nb_rmn = riemannian_samples(True, True)[100000] ekeys = sorted(euclid.keys(), reverse=False) rkeys = sorted(rmn.keys(), reverse=False) labels = ['Euclid. {}'.format(t) for t in ekeys] + ['Thresh. {:.0e}'.format(t) for t in rkeys] for vidx in range(1, 4): labels = ['Euclid. {}'.format(t) for t in ekeys] + ['Thresh. {:.0e}'.format(t) for t in rkeys] fig = plt.figure() ax = fig.add_subplot(111) num_breaks = 20 ess = {} for t in ekeys: breaks = np.split(euclid[t]['samples'][:, [-vidx]], num_breaks, axis=0) k = 'euclid-{}'.format(t) ess[k] = [] for i, b in enumerate(breaks): metrics = summarize(b) m = metrics['ess'].min() / (euclid[t]['time'] / num_breaks) ess[k].append(m) ax.violinplot([ess[k] for k in ess.keys()], showmeans=True, showmedians=True, showextrema=False) ess = {} for t in rkeys: breaks = np.split(rmn[t]['samples'][:, [-vidx]], num_breaks, axis=0) k = 'rmn-{}'.format(t) ess[k] = [] for i, b in enumerate(breaks): metrics = summarize(b) m = metrics['ess'].min() / (rmn[t]['time'] / num_breaks) ess[k].append(m) vpb = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 2, showmeans=True, showmedians=True, showextrema=False) ax.set_xticks(np.arange(1, len(labels) + 1)) ax.set_xticklabels(['' for l in labels]) ax.set_xticklabels(labels) ax.set_xlim(0.25, len(labels) + 0.75) for tick in ax.get_xticklabels(): tick.set_rotation(90) ax.axvline(len(ekeys) + 0.5, color='black', linestyle='--') ax.set_xlabel('') ax.set_ylabel('ESS / Sec.', fontsize=20) ax.tick_params(axis='x', labelsize=20) ax.tick_params(axis='y', labelsize=20) ax.grid(linestyle=':') fig.tight_layout() fig.savefig(os.path.join('images', 'minimum-ess-per-second-{}.pdf'.format(vidx))) labels = ['Thresh. {:.0e}'.format(t) for t in rkeys] fig = plt.figure() ax = fig.add_subplot(111) num_breaks = 20 ess = {} for t in rkeys: breaks = np.split(rmn[t]['samples'][:, [-vidx]], num_breaks, axis=0) k = 'rmn-{}'.format(t) ess[k] = [] for i, b in enumerate(breaks): metrics = summarize(b) m = metrics['ess'].min() / (rmn[t]['time'] / num_breaks) ess[k].append(m) vpb = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 1, showmeans=True, showmedians=True, showextrema=False) ess = {} for t in rkeys: breaks = np.split(nm_rmn[t]['samples'][:, [-vidx]], num_breaks, axis=0) k = 'rmn-{}'.format(t) ess[k] = [] for i, b in enumerate(breaks): metrics = summarize(b) m = metrics['ess'].min() / (nm_rmn[t]['time'] / num_breaks) ess[k].append(m) vpc = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 1, showmeans=True, showmedians=True, showextrema=False) ess = {} for t in rkeys: breaks = np.split(nb_rmn[t]['samples'][:, [-vidx]], num_breaks, axis=0) k = 'rmn-{}'.format(t) ess[k] = [] for i, b in enumerate(breaks): metrics = summarize(b) m = metrics['ess'].min() / (nb_rmn[t]['time'] / num_breaks) ess[k].append(m) vpd = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 1, showmeans=True, showmedians=True, showextrema=False) ax.set_xticks(np.arange(1, len(labels) + 1)) ax.set_xticklabels(['' for l in labels]) ax.set_xticklabels(labels) ax.set_xlim(0.25, len(labels) + 0.75) for tick in ax.get_xticklabels(): tick.set_rotation(90) ax.set_xlabel('') ax.set_ylabel('ESS / Sec.', fontsize=20) ax.tick_params(axis='x', labelsize=20) ax.tick_params(axis='y', labelsize=20) ax.grid(linestyle=':') if vidx == 1: ax.legend([vpb["bodies"][0], vpc["bodies"][0], vpd["bodies"][0]], [r'Fixed Point', r'Newton (Mom.)', r'Newton (Mom. and Pos.)'], fontsize=16, loc='upper left') fig.tight_layout() fig.savefig(os.path.join('images', 'minimum-ess-per-second-vs-newton-{}.pdf'.format(vidx))) def kolmogorov_smirnov(): euclid = euclidean_samples()[100000] rmn = riemannian_samples()[100000] nm_rmn = riemannian_samples(True)[100000] nb_rmn = riemannian_samples(True, True)[100000] iid = iid_samples() num_iid_ks = 100 iid_ks = np.zeros(num_iid_ks) x, y = iid[0], iid[1] for i in range(num_iid_ks): u = np.random.normal(size=x.shape[-1]) u = u / np.linalg.norm(u) iid_ks[i] = spst.ks_2samp(x@u, y@u).statistic print(iid_ks) summarize(x) summarize(y) summarize(rmn[1e-8]['samples']) print(list(rmn.keys())) ekeys = sorted(euclid.keys(), reverse=False) rkeys = sorted(rmn.keys(), reverse=False) labels = ['I.I.D.'] + ['Euclid. {}'.format(t) for t in ekeys] + ['Thresh. {:.0e}'.format(t) for t in rkeys] fig = plt.figure(figsize=(10, 4)) ax = fig.add_subplot(111) ax.violinplot([np.log10(iid_ks)], showmeans=True, showmedians=True, showextrema=False) ess = {} for t in ekeys: k = 'euclid-{}'.format(t) ess[k] = np.log10(euclid[t]['ks']) vpa = ax.violinplot([ess[k] for k in ess.keys()], positions=np.array([2.0]), showmeans=True, showmedians=True, showextrema=False) ess = {} for t in rkeys: k = 'rmn-{}'.format(t) ess[k] = np.log10(rmn[t]['ks']) vpb = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 3, showmeans=True, showmedians=True, showextrema=False) ax.set_xticks(np.arange(1, len(labels) + 1)) ax.set_xticklabels(['' for l in labels]) ax.set_xticklabels(labels, rotation=90, ha='right', fontsize=16) ax.set_xlim(0.25, len(labels) + 0.75) ax.axvline(len(ekeys) + 1.5, color='black', linestyle='--') ax.set_xlabel('') ax.set_ylabel('KS Statistic', fontsize=16) ax.tick_params(axis='y', labelsize=16) ax.grid(linestyle=':') fig.tight_layout() fig.savefig(os.path.join('images', 'kolmogorov-smirnov.pdf')) labels = ['Thresh. {:.0e}'.format(t) for t in rkeys] fig = plt.figure() ax = fig.add_subplot(111) ess = {} for t in rkeys: k = 'rmn-{}'.format(t) ess[k] = np.log10(rmn[t]['ks']) vpb = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 1, showmeans=True, showmedians=True, showextrema=False) ess = {} for t in rkeys: k = 'rmn-{}'.format(t) ess[k] = np.log10(nm_rmn[t]['ks']) vpc = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 1, showmeans=True, showmedians=True, showextrema=False) ess = {} for t in rkeys: k = 'rmn-{}'.format(t) ess[k] = np.log10(nb_rmn[t]['ks']) vpd = ax.violinplot([ess[k] for k in ess.keys()], positions=np.arange(len(rkeys)) + 1, showmeans=True, showmedians=True, showextrema=False) ax.set_xticks(np.arange(1, len(labels) + 1)) ax.set_xticklabels(['' for l in labels]) ax.set_xticklabels(labels, rotation=90, ha='right', fontsize=24) ax.set_xlim(0.25, len(labels) + 0.75) ax.set_xlabel('') ax.set_ylabel('KS Statistic', fontsize=30) ax.tick_params(axis='y', labelsize=24) ax.grid(linestyle=':') fig.tight_layout() fig.savefig(os.path.join('images', 'kolmogorov-smirnov-vs-newton.pdf')) def mmd(): euclid = euclidean_samples()[100000] rmn = riemannian_samples()[100000] ekeys = sorted(euclid.keys(), reverse=False) rkeys = sorted(rmn.keys(), reverse=False) num_thresholds = len(rkeys) thresholds = np.array(rkeys) emmd = np.log10(np.abs(np.array([euclid[k]['mmd'] for k in ekeys]))) rmmd = np.log10(np.abs(np.array([rmn[k]['mmd'] for k in rkeys]))) fig = plt.figure() ax = fig.add_subplot(111) ax.plot(rmmd, '.-') for v in emmd: ax.axhline(v, color='k') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(0, num_thresholds)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.grid(linestyle=':') ax.set_xlabel(r'$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel(r'$\log_{10}|\mathrm{MMD}^2|$ Estimate', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'mmd.pdf')) def wasserstein_sliced(): euclid = euclidean_samples()[100000] rmn = riemannian_samples()[100000] ekeys = sorted(euclid.keys(), reverse=False) rkeys = sorted(rmn.keys(), reverse=False) num_thresholds = len(rkeys) thresholds = np.array(rkeys) esw = np.log10(np.abs(np.array([euclid[k]['sw'] for k in ekeys]))) rsw = np.log10(np.abs(np.array([rmn[k]['sw'] for k in rkeys]))) fig = plt.figure() ax = fig.add_subplot(111) ax.plot(rsw, '.-') for v in esw: ax.axhline(v, color='k') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(0, num_thresholds)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.grid(linestyle=':') ax.set_xlabel(r'$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel(r'$\log_{10}$ Sliced Wasserstein', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'sw.pdf')) def volume_preservation(): euclid = euclidean_samples() rmn = riemannian_samples() num_thresholds = 9 thresholds = np.logspace(-num_thresholds, -1, num_thresholds) dat = [rmn[100000][t]['jacdet'][1e-5] for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] fig = plt.figure() ax = fig.add_subplot(111) ax.boxplot(dat, notch=True) ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Vol. Pres. Err.', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'jacobian-determinant.pdf')) fig = plt.figure() ax = fig.add_subplot(111) bp = ax.boxplot(dat, notch=True, patch_artist=True) for patch in bp['boxes']: patch.set(facecolor='tab:blue') nm_rmn = riemannian_samples(True) dat = [nm_rmn[100000][t]['jacdet'][1e-5] for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] nm_bp = ax.boxplot(dat, notch=True, patch_artist=True) for patch in nm_bp['boxes']: patch.set(facecolor='tab:red') nb_rmn = riemannian_samples(True, True) dat = [nb_rmn[100000][t]['jacdet'][1e-5] for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] nb_bp = ax.boxplot(dat, notch=True, patch_artist=True) for patch in nb_bp['boxes']: patch.set(facecolor='tab:green') ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Vol. Pres. Err.', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'jacobian-determinant-vs-newton.pdf')) perturb = sorted(rmn[100000][1e-9]['jacdet'].keys()) num_perturb = len(perturb) dat = [rmn[100000][1e-9]['jacdet'][p] for p in perturb] dat = [_[~np.isnan(_)] for _ in dat] fig = plt.figure() ax = fig.add_subplot(111) ax.boxplot(dat, notch=True) ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_perturb + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in perturb], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, num_perturb + 0.75) ax.set_xlabel('$\log_{10}$ Perturbation', fontsize=30) ax.set_ylabel('$\log_{10}$ Volume Preservation Error', fontsize=20) fig.tight_layout() fig.savefig(os.path.join('images', 'perturbation.pdf')) def reversibility(): euclid = euclidean_samples() rmn = riemannian_samples() num_thresholds = 9 thresholds = np.logspace(-num_thresholds, -1, num_thresholds) dat = [rmn[100000][t]['absrev'] for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] fig = plt.figure() ax = fig.add_subplot(111) ax.boxplot(dat, notch=True) ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Abs. Rev. Error', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'absolute-reversibility.pdf')) fig = plt.figure() ax = fig.add_subplot(111) bp = ax.boxplot(dat, notch=True, patch_artist=True) for patch in bp['boxes']: patch.set(facecolor='tab:blue') nm_rmn = riemannian_samples(True) dat = [nm_rmn[100000][t]['absrev'] for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] nm_bp = ax.boxplot(dat, notch=True, patch_artist=True) for patch in nm_bp['boxes']: patch.set(facecolor='tab:red') nb_rmn = riemannian_samples(True, True) dat = [nb_rmn[100000][t]['absrev'] for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] nb_bp = ax.boxplot(dat, notch=True, patch_artist=True) for patch in nb_bp['boxes']: patch.set(facecolor='tab:green') ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Abs. Rev. Err.', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'absolute-reversibility-vs-newton.pdf')) dat = [rmn[100000][t]['relrev'] for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] fig = plt.figure() ax = fig.add_subplot(111) ax.boxplot(dat, notch=True) ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Rel. Rev. Error', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'relative-reversibility.pdf')) def momentum_fixed_point(): euclid = euclidean_samples() rmn = riemannian_samples() num_thresholds = 9 thresholds = np.logspace(-num_thresholds, -1, num_thresholds) dat = [np.log10(rmn[100000][t]['nfp_mom']) for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] dat = [_[np.random.permutation(len(_))[:10000]] for _ in dat] fig = plt.figure() ax = fig.add_subplot(111) ax.boxplot(dat, notch=True) ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Mom. Fixed Point', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'num-fixed-point-momentum.pdf')) nrmn = riemannian_samples(True) dat = [np.log10(rmn[100000][t]['nfp_mom']) for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] mean = np.array([np.mean(_) for _ in dat]) std = np.array([np.std(_) for _ in dat]) ndat = [np.log10(nrmn[100000][t]['nfp_mom']) for t in thresholds] ndat = [_[~np.isnan(_)] for _ in ndat] nmean = np.array([np.mean(_) for _ in ndat]) nstd = np.array([np.std(_) for _ in ndat]) fig = plt.figure() ax = fig.add_subplot(111) ax.plot(np.arange(1, num_thresholds + 1), mean, color='tab:blue', label='Fixed Point') ax.plot(np.arange(1, num_thresholds + 1), mean + std, '--', color='tab:blue') ax.plot(np.arange(1, num_thresholds + 1), mean - std, '--', color='tab:blue') ax.plot(np.arange(1, num_thresholds + 1), nmean, color='tab:orange', label='Newton') ax.plot(np.arange(1, num_thresholds + 1), nmean + nstd, '--', color='tab:orange') ax.plot(np.arange(1, num_thresholds + 1), nmean - nstd, '--', color='tab:orange') ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Momentum Fixed Point', fontsize=20) ax.set_ylim((0.0, 1.1)) ax.legend(fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'num-fixed-point-momentum-vs-newton.pdf')) def position_fixed_point(): euclid = euclidean_samples() rmn = riemannian_samples() nrmn = riemannian_samples(True, True) num_thresholds = 9 thresholds = np.logspace(-num_thresholds, -1, num_thresholds) dat = [np.log10(rmn[100000][t]['nfp_pos']) for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] dat = [_[np.random.permutation(len(_))[:10000]] for _ in dat] fig = plt.figure() ax = fig.add_subplot(111) ax.boxplot(dat, notch=True) ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Pos. Fixed Point', fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'num-fixed-point-position.pdf')) dat = [np.log10(rmn[100000][t]['nfp_pos']) for t in thresholds] dat = [_[~np.isnan(_)] for _ in dat] mean = np.array([np.mean(_) for _ in dat]) std = np.array([np.std(_) for _ in dat]) ndat = [np.log10(nrmn[100000][t]['nfp_pos']) for t in thresholds] ndat = [_[~np.isnan(_)] for _ in ndat] nmean = np.array([np.mean(_) for _ in ndat]) nstd = np.array([np.std(_) for _ in ndat]) fig = plt.figure() ax = fig.add_subplot(111) ax.plot(np.arange(1, num_thresholds + 1), mean, color='tab:blue', label='Fixed Point') ax.plot(np.arange(1, num_thresholds + 1), mean + std, '--', color='tab:blue') ax.plot(np.arange(1, num_thresholds + 1), mean - std, '--', color='tab:blue') ax.plot(np.arange(1, num_thresholds + 1), nmean, color='tab:orange', label='Newton') ax.plot(np.arange(1, num_thresholds + 1), nmean + nstd, '--', color='tab:orange') ax.plot(np.arange(1, num_thresholds + 1), nmean - nstd, '--', color='tab:orange') ax.grid(linestyle=':') ax.xaxis.set_tick_params(direction='out') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(np.arange(1, num_thresholds + 1)) ax.set_xticklabels(['{:.0f}'.format(np.log10(t)) for t in thresholds], fontsize=24) ax.tick_params(axis='y', labelsize=24) ax.set_xlim(0.25, len(thresholds) + 0.75) ax.set_xlabel('$\log_{10}$ Threshold', fontsize=30) ax.set_ylabel('$\log_{10}$ Position Fixed Point', fontsize=20) ax.set_ylim((0.0, 1.1)) ax.legend(fontsize=30) fig.tight_layout() fig.savefig(os.path.join('images', 'num-fixed-point-position-vs-newton.pdf')) def main(): kolmogorov_smirnov() exit() momentum_fixed_point() position_fixed_point() wasserstein_sliced() mmd() fitzhugh_nagumo() effective_sample_size_per_second() effective_sample_size() volume_preservation() reversibility() if __name__ == '__main__': main()

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Python

mat_db/main/migrations/0006_hosedynamic_nu_min40_hosedynamic_nu_plus100_and_more.py

tkminek/material_database

8661617077192d20e8d9445cd6560bf1266f0582

[ "MIT" ]

null

mat_db/main/migrations/0006_hosedynamic_nu_min40_hosedynamic_nu_plus100_and_more.py

tkminek/material_database

8661617077192d20e8d9445cd6560bf1266f0582

[ "MIT" ]

null

mat_db/main/migrations/0006_hosedynamic_nu_min40_hosedynamic_nu_plus100_and_more.py

tkminek/material_database

8661617077192d20e8d9445cd6560bf1266f0582

[ "MIT" ]

null

# Generated by Django 4.0.2 on 2022-02-23 10:19 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('main', '0005_hose_hosestatic_hosedynamic'), ] operations = [ migrations.AddField( model_name='hosedynamic', name='nu_min40', field=models.FloatField(default=0.495), ), migrations.AddField( model_name='hosedynamic', name='nu_plus100', field=models.FloatField(default=0.495), ), migrations.AddField( model_name='hosedynamic', name='nu_plus23', field=models.FloatField(default=0.495), ), migrations.AddField( model_name='hosestatic', name='nu_min40', field=models.FloatField(default=0.495), ), migrations.AddField( model_name='hosestatic', name='nu_plus100', field=models.FloatField(default=0.495), ), migrations.AddField( model_name='hosestatic', name='nu_plus23', field=models.FloatField(default=0.495), ), ]

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